MagickCore  7.1.0
morphology.c
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1 /*
2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3 % %
4 % %
5 % %
6 % M M OOO RRRR PPPP H H OOO L OOO GGGG Y Y %
7 % MM MM O O R R P P H H O O L O O G Y Y %
8 % M M M O O RRRR PPPP HHHHH O O L O O G GGG Y %
9 % M M O O R R P H H O O L O O G G Y %
10 % M M OOO R R P H H OOO LLLLL OOO GGG Y %
11 % %
12 % %
13 % MagickCore Morphology Methods %
14 % %
15 % Software Design %
16 % Anthony Thyssen %
17 % January 2010 %
18 % %
19 % %
20 % Copyright 1999-2021 ImageMagick Studio LLC, a non-profit organization %
21 % dedicated to making software imaging solutions freely available. %
22 % %
23 % You may not use this file except in compliance with the License. You may %
24 % obtain a copy of the License at %
25 % %
26 % https://imagemagick.org/script/license.php %
27 % %
28 % Unless required by applicable law or agreed to in writing, software %
29 % distributed under the License is distributed on an "AS IS" BASIS, %
30 % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
31 % See the License for the specific language governing permissions and %
32 % limitations under the License. %
33 % %
34 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
35 %
36 % Morphology is the application of various kernels, of any size or shape, to an
37 % image in various ways (typically binary, but not always).
38 %
39 % Convolution (weighted sum or average) is just one specific type of
40 % morphology. Just one that is very common for image bluring and sharpening
41 % effects. Not only 2D Gaussian blurring, but also 2-pass 1D Blurring.
42 %
43 % This module provides not only a general morphology function, and the ability
44 % to apply more advanced or iterative morphologies, but also functions for the
45 % generation of many different types of kernel arrays from user supplied
46 % arguments. Prehaps even the generation of a kernel from a small image.
47 */
48 
49 /*
50  Include declarations.
51 */
52 #include "MagickCore/studio.h"
53 #include "MagickCore/artifact.h"
54 #include "MagickCore/cache-view.h"
55 #include "MagickCore/channel.h"
57 #include "MagickCore/enhance.h"
58 #include "MagickCore/exception.h"
60 #include "MagickCore/gem.h"
61 #include "MagickCore/gem-private.h"
62 #include "MagickCore/image.h"
64 #include "MagickCore/linked-list.h"
65 #include "MagickCore/list.h"
66 #include "MagickCore/magick.h"
67 #include "MagickCore/memory_.h"
70 #include "MagickCore/morphology.h"
72 #include "MagickCore/option.h"
74 #include "MagickCore/prepress.h"
75 #include "MagickCore/quantize.h"
76 #include "MagickCore/resource_.h"
77 #include "MagickCore/registry.h"
78 #include "MagickCore/semaphore.h"
79 #include "MagickCore/splay-tree.h"
80 #include "MagickCore/statistic.h"
81 #include "MagickCore/string_.h"
84 #include "MagickCore/token.h"
85 #include "MagickCore/utility.h"
87 
88 /*
89  Other global definitions used by module.
90 */
91 #define Minimize(assign,value) assign=MagickMin(assign,value)
92 #define Maximize(assign,value) assign=MagickMax(assign,value)
93 
94 /* Integer Factorial Function - for a Binomial kernel */
95 #if 1
96 static inline size_t fact(size_t n)
97 {
98  size_t f,l;
99  for(f=1, l=2; l <= n; f=f*l, l++);
100  return(f);
101 }
102 #elif 1 /* glibc floating point alternatives */
103 #define fact(n) ((size_t)tgamma((double)n+1))
104 #else
105 #define fact(n) ((size_t)lgamma((double)n+1))
106 #endif
107 
108 
109 /* Currently these are only internal to this module */
110 static void
113  ExpandRotateKernelInfo(KernelInfo *, const double),
114  RotateKernelInfo(KernelInfo *, double);
115 
116 
117 /* Quick function to find last kernel in a kernel list */
118 static inline KernelInfo *LastKernelInfo(KernelInfo *kernel)
119 {
120  while (kernel->next != (KernelInfo *) NULL)
121  kernel=kernel->next;
122  return(kernel);
123 }
124 
125 /*
126 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
127 % %
128 % %
129 % %
130 % A c q u i r e K e r n e l I n f o %
131 % %
132 % %
133 % %
134 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
135 %
136 % AcquireKernelInfo() takes the given string (generally supplied by the
137 % user) and converts it into a Morphology/Convolution Kernel. This allows
138 % users to specify a kernel from a number of pre-defined kernels, or to fully
139 % specify their own kernel for a specific Convolution or Morphology
140 % Operation.
141 %
142 % The kernel so generated can be any rectangular array of floating point
143 % values (doubles) with the 'control point' or 'pixel being affected'
144 % anywhere within that array of values.
145 %
146 % Previously IM was restricted to a square of odd size using the exact
147 % center as origin, this is no longer the case, and any rectangular kernel
148 % with any value being declared the origin. This in turn allows the use of
149 % highly asymmetrical kernels.
150 %
151 % The floating point values in the kernel can also include a special value
152 % known as 'nan' or 'not a number' to indicate that this value is not part
153 % of the kernel array. This allows you to shaped the kernel within its
154 % rectangular area. That is 'nan' values provide a 'mask' for the kernel
155 % shape. However at least one non-nan value must be provided for correct
156 % working of a kernel.
157 %
158 % The returned kernel should be freed using the DestroyKernelInfo() when you
159 % are finished with it. Do not free this memory yourself.
160 %
161 % Input kernel defintion strings can consist of any of three types.
162 %
163 % "name:args[[@><]"
164 % Select from one of the built in kernels, using the name and
165 % geometry arguments supplied. See AcquireKernelBuiltIn()
166 %
167 % "WxH[+X+Y][@><]:num, num, num ..."
168 % a kernel of size W by H, with W*H floating point numbers following.
169 % the 'center' can be optionally be defined at +X+Y (such that +0+0
170 % is top left corner). If not defined the pixel in the center, for
171 % odd sizes, or to the immediate top or left of center for even sizes
172 % is automatically selected.
173 %
174 % "num, num, num, num, ..."
175 % list of floating point numbers defining an 'old style' odd sized
176 % square kernel. At least 9 values should be provided for a 3x3
177 % square kernel, 25 for a 5x5 square kernel, 49 for 7x7, etc.
178 % Values can be space or comma separated. This is not recommended.
179 %
180 % You can define a 'list of kernels' which can be used by some morphology
181 % operators A list is defined as a semi-colon separated list kernels.
182 %
183 % " kernel ; kernel ; kernel ; "
184 %
185 % Any extra ';' characters, at start, end or between kernel defintions are
186 % simply ignored.
187 %
188 % The special flags will expand a single kernel, into a list of rotated
189 % kernels. A '@' flag will expand a 3x3 kernel into a list of 45-degree
190 % cyclic rotations, while a '>' will generate a list of 90-degree rotations.
191 % The '<' also exands using 90-degree rotates, but giving a 180-degree
192 % reflected kernel before the +/- 90-degree rotations, which can be important
193 % for Thinning operations.
194 %
195 % Note that 'name' kernels will start with an alphabetic character while the
196 % new kernel specification has a ':' character in its specification string.
197 % If neither is the case, it is assumed an old style of a simple list of
198 % numbers generating a odd-sized square kernel has been given.
199 %
200 % The format of the AcquireKernal method is:
201 %
202 % KernelInfo *AcquireKernelInfo(const char *kernel_string)
203 %
204 % A description of each parameter follows:
205 %
206 % o kernel_string: the Morphology/Convolution kernel wanted.
207 %
208 */
209 
210 /* This was separated so that it could be used as a separate
211 ** array input handling function, such as for -color-matrix
212 */
213 static KernelInfo *ParseKernelArray(const char *kernel_string)
214 {
215  KernelInfo
216  *kernel;
217 
218  char
219  token[MagickPathExtent];
220 
221  const char
222  *p,
223  *end;
224 
225  ssize_t
226  i;
227 
228  double
229  nan = sqrt((double)-1.0); /* Special Value : Not A Number */
230 
232  flags;
233 
235  args;
236 
237  kernel=(KernelInfo *) AcquireMagickMemory(sizeof(*kernel));
238  if (kernel == (KernelInfo *) NULL)
239  return(kernel);
240  (void) memset(kernel,0,sizeof(*kernel));
241  kernel->minimum = kernel->maximum = kernel->angle = 0.0;
242  kernel->negative_range = kernel->positive_range = 0.0;
243  kernel->type = UserDefinedKernel;
244  kernel->next = (KernelInfo *) NULL;
246  if (kernel_string == (const char *) NULL)
247  return(kernel);
248 
249  /* find end of this specific kernel definition string */
250  end = strchr(kernel_string, ';');
251  if ( end == (char *) NULL )
252  end = strchr(kernel_string, '\0');
253 
254  /* clear flags - for Expanding kernel lists thorugh rotations */
255  flags = NoValue;
256 
257  /* Has a ':' in argument - New user kernel specification
258  FUTURE: this split on ':' could be done by StringToken()
259  */
260  p = strchr(kernel_string, ':');
261  if ( p != (char *) NULL && p < end)
262  {
263  /* ParseGeometry() needs the geometry separated! -- Arrgghh */
264  memcpy(token, kernel_string, (size_t) (p-kernel_string));
265  token[p-kernel_string] = '\0';
266  SetGeometryInfo(&args);
267  flags = ParseGeometry(token, &args);
268 
269  /* Size handling and checks of geometry settings */
270  if ( (flags & WidthValue) == 0 ) /* if no width then */
271  args.rho = args.sigma; /* then width = height */
272  if ( args.rho < 1.0 ) /* if width too small */
273  args.rho = 1.0; /* then width = 1 */
274  if ( args.sigma < 1.0 ) /* if height too small */
275  args.sigma = args.rho; /* then height = width */
276  kernel->width = (size_t)args.rho;
277  kernel->height = (size_t)args.sigma;
278 
279  /* Offset Handling and Checks */
280  if ( args.xi < 0.0 || args.psi < 0.0 )
281  return(DestroyKernelInfo(kernel));
282  kernel->x = ((flags & XValue)!=0) ? (ssize_t)args.xi
283  : (ssize_t) (kernel->width-1)/2;
284  kernel->y = ((flags & YValue)!=0) ? (ssize_t)args.psi
285  : (ssize_t) (kernel->height-1)/2;
286  if ( kernel->x >= (ssize_t) kernel->width ||
287  kernel->y >= (ssize_t) kernel->height )
288  return(DestroyKernelInfo(kernel));
289 
290  p++; /* advance beyond the ':' */
291  }
292  else
293  { /* ELSE - Old old specification, forming odd-square kernel */
294  /* count up number of values given */
295  p=(const char *) kernel_string;
296  while ((isspace((int) ((unsigned char) *p)) != 0) || (*p == '\''))
297  p++; /* ignore "'" chars for convolve filter usage - Cristy */
298  for (i=0; p < end; i++)
299  {
300  (void) GetNextToken(p,&p,MagickPathExtent,token);
301  if (*token == ',')
302  (void) GetNextToken(p,&p,MagickPathExtent,token);
303  }
304  /* set the size of the kernel - old sized square */
305  kernel->width = kernel->height= (size_t) sqrt((double) i+1.0);
306  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
307  p=(const char *) kernel_string;
308  while ((isspace((int) ((unsigned char) *p)) != 0) || (*p == '\''))
309  p++; /* ignore "'" chars for convolve filter usage - Cristy */
310  }
311 
312  /* Read in the kernel values from rest of input string argument */
314  kernel->width,kernel->height*sizeof(*kernel->values)));
315  if (kernel->values == (MagickRealType *) NULL)
316  return(DestroyKernelInfo(kernel));
317  kernel->minimum=MagickMaximumValue;
318  kernel->maximum=(-MagickMaximumValue);
319  kernel->negative_range = kernel->positive_range = 0.0;
320  for (i=0; (i < (ssize_t) (kernel->width*kernel->height)) && (p < end); i++)
321  {
322  (void) GetNextToken(p,&p,MagickPathExtent,token);
323  if (*token == ',')
324  (void) GetNextToken(p,&p,MagickPathExtent,token);
325  if ( LocaleCompare("nan",token) == 0
326  || LocaleCompare("-",token) == 0 ) {
327  kernel->values[i] = nan; /* this value is not part of neighbourhood */
328  }
329  else {
330  kernel->values[i] = StringToDouble(token,(char **) NULL);
331  ( kernel->values[i] < 0)
332  ? ( kernel->negative_range += kernel->values[i] )
333  : ( kernel->positive_range += kernel->values[i] );
334  Minimize(kernel->minimum, kernel->values[i]);
335  Maximize(kernel->maximum, kernel->values[i]);
336  }
337  }
338 
339  /* sanity check -- no more values in kernel definition */
340  (void) GetNextToken(p,&p,MagickPathExtent,token);
341  if ( *token != '\0' && *token != ';' && *token != '\'' )
342  return(DestroyKernelInfo(kernel));
343 
344 #if 0
345  /* this was the old method of handling a incomplete kernel */
346  if ( i < (ssize_t) (kernel->width*kernel->height) ) {
347  Minimize(kernel->minimum, kernel->values[i]);
348  Maximize(kernel->maximum, kernel->values[i]);
349  for ( ; i < (ssize_t) (kernel->width*kernel->height); i++)
350  kernel->values[i]=0.0;
351  }
352 #else
353  /* Number of values for kernel was not enough - Report Error */
354  if ( i < (ssize_t) (kernel->width*kernel->height) )
355  return(DestroyKernelInfo(kernel));
356 #endif
357 
358  /* check that we recieved at least one real (non-nan) value! */
359  if (kernel->minimum == MagickMaximumValue)
360  return(DestroyKernelInfo(kernel));
361 
362  if ( (flags & AreaValue) != 0 ) /* '@' symbol in kernel size */
363  ExpandRotateKernelInfo(kernel, 45.0); /* cyclic rotate 3x3 kernels */
364  else if ( (flags & GreaterValue) != 0 ) /* '>' symbol in kernel args */
365  ExpandRotateKernelInfo(kernel, 90.0); /* 90 degree rotate of kernel */
366  else if ( (flags & LessValue) != 0 ) /* '<' symbol in kernel args */
367  ExpandMirrorKernelInfo(kernel); /* 90 degree mirror rotate */
368 
369  return(kernel);
370 }
371 
372 static KernelInfo *ParseKernelName(const char *kernel_string,
373  ExceptionInfo *exception)
374 {
375  char
376  token[MagickPathExtent];
377 
378  const char
379  *p,
380  *end;
381 
383  args;
384 
385  KernelInfo
386  *kernel;
387 
389  flags;
390 
391  ssize_t
392  type;
393 
394  /* Parse special 'named' kernel */
395  (void) GetNextToken(kernel_string,&p,MagickPathExtent,token);
397  if ( type < 0 || type == UserDefinedKernel )
398  return((KernelInfo *) NULL); /* not a valid named kernel */
399 
400  while (((isspace((int) ((unsigned char) *p)) != 0) ||
401  (*p == ',') || (*p == ':' )) && (*p != '\0') && (*p != ';'))
402  p++;
403 
404  end = strchr(p, ';'); /* end of this kernel defintion */
405  if ( end == (char *) NULL )
406  end = strchr(p, '\0');
407 
408  /* ParseGeometry() needs the geometry separated! -- Arrgghh */
409  memcpy(token, p, (size_t) (end-p));
410  token[end-p] = '\0';
411  SetGeometryInfo(&args);
412  flags = ParseGeometry(token, &args);
413 
414 #if 0
415  /* For Debugging Geometry Input */
416  (void) FormatLocaleFile(stderr, "Geometry = 0x%04X : %lg x %lg %+lg %+lg\n",
417  flags, args.rho, args.sigma, args.xi, args.psi );
418 #endif
419 
420  /* special handling of missing values in input string */
421  switch( type ) {
422  /* Shape Kernel Defaults */
423  case UnityKernel:
424  if ( (flags & WidthValue) == 0 )
425  args.rho = 1.0; /* Default scale = 1.0, zero is valid */
426  break;
427  case SquareKernel:
428  case DiamondKernel:
429  case OctagonKernel:
430  case DiskKernel:
431  case PlusKernel:
432  case CrossKernel:
433  if ( (flags & HeightValue) == 0 )
434  args.sigma = 1.0; /* Default scale = 1.0, zero is valid */
435  break;
436  case RingKernel:
437  if ( (flags & XValue) == 0 )
438  args.xi = 1.0; /* Default scale = 1.0, zero is valid */
439  break;
440  case RectangleKernel: /* Rectangle - set size defaults */
441  if ( (flags & WidthValue) == 0 ) /* if no width then */
442  args.rho = args.sigma; /* then width = height */
443  if ( args.rho < 1.0 ) /* if width too small */
444  args.rho = 3; /* then width = 3 */
445  if ( args.sigma < 1.0 ) /* if height too small */
446  args.sigma = args.rho; /* then height = width */
447  if ( (flags & XValue) == 0 ) /* center offset if not defined */
448  args.xi = (double)(((ssize_t)args.rho-1)/2);
449  if ( (flags & YValue) == 0 )
450  args.psi = (double)(((ssize_t)args.sigma-1)/2);
451  break;
452  /* Distance Kernel Defaults */
453  case ChebyshevKernel:
454  case ManhattanKernel:
455  case OctagonalKernel:
456  case EuclideanKernel:
457  if ( (flags & HeightValue) == 0 ) /* no distance scale */
458  args.sigma = 100.0; /* default distance scaling */
459  else if ( (flags & AspectValue ) != 0 ) /* '!' flag */
460  args.sigma = QuantumRange/(args.sigma+1); /* maximum pixel distance */
461  else if ( (flags & PercentValue ) != 0 ) /* '%' flag */
462  args.sigma *= QuantumRange/100.0; /* percentage of color range */
463  break;
464  default:
465  break;
466  }
467 
468  kernel = AcquireKernelBuiltIn((KernelInfoType)type, &args, exception);
469  if ( kernel == (KernelInfo *) NULL )
470  return(kernel);
471 
472  /* global expand to rotated kernel list - only for single kernels */
473  if ( kernel->next == (KernelInfo *) NULL ) {
474  if ( (flags & AreaValue) != 0 ) /* '@' symbol in kernel args */
475  ExpandRotateKernelInfo(kernel, 45.0);
476  else if ( (flags & GreaterValue) != 0 ) /* '>' symbol in kernel args */
477  ExpandRotateKernelInfo(kernel, 90.0);
478  else if ( (flags & LessValue) != 0 ) /* '<' symbol in kernel args */
479  ExpandMirrorKernelInfo(kernel);
480  }
481 
482  return(kernel);
483 }
484 
485 MagickExport KernelInfo *AcquireKernelInfo(const char *kernel_string,
486  ExceptionInfo *exception)
487 {
488  KernelInfo
489  *kernel,
490  *new_kernel;
491 
492  char
493  *kernel_cache,
494  token[MagickPathExtent];
495 
496  const char
497  *p;
498 
499  if (kernel_string == (const char *) NULL)
500  return(ParseKernelArray(kernel_string));
501  p=kernel_string;
502  kernel_cache=(char *) NULL;
503  if (*kernel_string == '@')
504  {
505  kernel_cache=FileToString(kernel_string+1,~0UL,exception);
506  if (kernel_cache == (char *) NULL)
507  return((KernelInfo *) NULL);
508  p=(const char *) kernel_cache;
509  }
510  kernel=NULL;
511  while (GetNextToken(p,(const char **) NULL,MagickPathExtent,token), *token != '\0')
512  {
513  /* ignore extra or multiple ';' kernel separators */
514  if (*token != ';')
515  {
516  /* tokens starting with alpha is a Named kernel */
517  if (isalpha((int) ((unsigned char) *token)) != 0)
518  new_kernel=ParseKernelName(p,exception);
519  else /* otherwise a user defined kernel array */
520  new_kernel=ParseKernelArray(p);
521 
522  /* Error handling -- this is not proper error handling! */
523  if (new_kernel == (KernelInfo *) NULL)
524  {
525  if (kernel != (KernelInfo *) NULL)
526  kernel=DestroyKernelInfo(kernel);
527  return((KernelInfo *) NULL);
528  }
529 
530  /* initialise or append the kernel list */
531  if (kernel == (KernelInfo *) NULL)
532  kernel=new_kernel;
533  else
534  LastKernelInfo(kernel)->next=new_kernel;
535  }
536 
537  /* look for the next kernel in list */
538  p=strchr(p,';');
539  if (p == (char *) NULL)
540  break;
541  p++;
542  }
543  if (kernel_cache != (char *) NULL)
544  kernel_cache=DestroyString(kernel_cache);
545  return(kernel);
546 }
547 
548 /*
549 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
550 % %
551 % %
552 % %
553 % A c q u i r e K e r n e l B u i l t I n %
554 % %
555 % %
556 % %
557 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
558 %
559 % AcquireKernelBuiltIn() returned one of the 'named' built-in types of
560 % kernels used for special purposes such as gaussian blurring, skeleton
561 % pruning, and edge distance determination.
562 %
563 % They take a KernelType, and a set of geometry style arguments, which were
564 % typically decoded from a user supplied string, or from a more complex
565 % Morphology Method that was requested.
566 %
567 % The format of the AcquireKernalBuiltIn method is:
568 %
569 % KernelInfo *AcquireKernelBuiltIn(const KernelInfoType type,
570 % const GeometryInfo args)
571 %
572 % A description of each parameter follows:
573 %
574 % o type: the pre-defined type of kernel wanted
575 %
576 % o args: arguments defining or modifying the kernel
577 %
578 % Convolution Kernels
579 %
580 % Unity
581 % The a No-Op or Scaling single element kernel.
582 %
583 % Gaussian:{radius},{sigma}
584 % Generate a two-dimensional gaussian kernel, as used by -gaussian.
585 % The sigma for the curve is required. The resulting kernel is
586 % normalized,
587 %
588 % If 'sigma' is zero, you get a single pixel on a field of zeros.
589 %
590 % NOTE: that the 'radius' is optional, but if provided can limit (clip)
591 % the final size of the resulting kernel to a square 2*radius+1 in size.
592 % The radius should be at least 2 times that of the sigma value, or
593 % sever clipping and aliasing may result. If not given or set to 0 the
594 % radius will be determined so as to produce the best minimal error
595 % result, which is usally much larger than is normally needed.
596 %
597 % LoG:{radius},{sigma}
598 % "Laplacian of a Gaussian" or "Mexician Hat" Kernel.
599 % The supposed ideal edge detection, zero-summing kernel.
600 %
601 % An alturnative to this kernel is to use a "DoG" with a sigma ratio of
602 % approx 1.6 (according to wikipedia).
603 %
604 % DoG:{radius},{sigma1},{sigma2}
605 % "Difference of Gaussians" Kernel.
606 % As "Gaussian" but with a gaussian produced by 'sigma2' subtracted
607 % from the gaussian produced by 'sigma1'. Typically sigma2 > sigma1.
608 % The result is a zero-summing kernel.
609 %
610 % Blur:{radius},{sigma}[,{angle}]
611 % Generates a 1 dimensional or linear gaussian blur, at the angle given
612 % (current restricted to orthogonal angles). If a 'radius' is given the
613 % kernel is clipped to a width of 2*radius+1. Kernel can be rotated
614 % by a 90 degree angle.
615 %
616 % If 'sigma' is zero, you get a single pixel on a field of zeros.
617 %
618 % Note that two convolutions with two "Blur" kernels perpendicular to
619 % each other, is equivalent to a far larger "Gaussian" kernel with the
620 % same sigma value, However it is much faster to apply. This is how the
621 % "-blur" operator actually works.
622 %
623 % Comet:{width},{sigma},{angle}
624 % Blur in one direction only, much like how a bright object leaves
625 % a comet like trail. The Kernel is actually half a gaussian curve,
626 % Adding two such blurs in opposite directions produces a Blur Kernel.
627 % Angle can be rotated in multiples of 90 degrees.
628 %
629 % Note that the first argument is the width of the kernel and not the
630 % radius of the kernel.
631 %
632 % Binomial:[{radius}]
633 % Generate a discrete kernel using a 2 dimentional Pascel's Triangle
634 % of values. Used for special forma of image filters.
635 %
636 % # Still to be implemented...
637 % #
638 % # Filter2D
639 % # Filter1D
640 % # Set kernel values using a resize filter, and given scale (sigma)
641 % # Cylindrical or Linear. Is this possible with an image?
642 % #
643 %
644 % Named Constant Convolution Kernels
645 %
646 % All these are unscaled, zero-summing kernels by default. As such for
647 % non-HDRI version of ImageMagick some form of normalization, user scaling,
648 % and biasing the results is recommended, to prevent the resulting image
649 % being 'clipped'.
650 %
651 % The 3x3 kernels (most of these) can be circularly rotated in multiples of
652 % 45 degrees to generate the 8 angled varients of each of the kernels.
653 %
654 % Laplacian:{type}
655 % Discrete Lapacian Kernels, (without normalization)
656 % Type 0 : 3x3 with center:8 surounded by -1 (8 neighbourhood)
657 % Type 1 : 3x3 with center:4 edge:-1 corner:0 (4 neighbourhood)
658 % Type 2 : 3x3 with center:4 edge:1 corner:-2
659 % Type 3 : 3x3 with center:4 edge:-2 corner:1
660 % Type 5 : 5x5 laplacian
661 % Type 7 : 7x7 laplacian
662 % Type 15 : 5x5 LoG (sigma approx 1.4)
663 % Type 19 : 9x9 LoG (sigma approx 1.4)
664 %
665 % Sobel:{angle}
666 % Sobel 'Edge' convolution kernel (3x3)
667 % | -1, 0, 1 |
668 % | -2, 0,-2 |
669 % | -1, 0, 1 |
670 %
671 % Roberts:{angle}
672 % Roberts convolution kernel (3x3)
673 % | 0, 0, 0 |
674 % | -1, 1, 0 |
675 % | 0, 0, 0 |
676 %
677 % Prewitt:{angle}
678 % Prewitt Edge convolution kernel (3x3)
679 % | -1, 0, 1 |
680 % | -1, 0, 1 |
681 % | -1, 0, 1 |
682 %
683 % Compass:{angle}
684 % Prewitt's "Compass" convolution kernel (3x3)
685 % | -1, 1, 1 |
686 % | -1,-2, 1 |
687 % | -1, 1, 1 |
688 %
689 % Kirsch:{angle}
690 % Kirsch's "Compass" convolution kernel (3x3)
691 % | -3,-3, 5 |
692 % | -3, 0, 5 |
693 % | -3,-3, 5 |
694 %
695 % FreiChen:{angle}
696 % Frei-Chen Edge Detector is based on a kernel that is similar to
697 % the Sobel Kernel, but is designed to be isotropic. That is it takes
698 % into account the distance of the diagonal in the kernel.
699 %
700 % | 1, 0, -1 |
701 % | sqrt(2), 0, -sqrt(2) |
702 % | 1, 0, -1 |
703 %
704 % FreiChen:{type},{angle}
705 %
706 % Frei-Chen Pre-weighted kernels...
707 %
708 % Type 0: default un-nomalized version shown above.
709 %
710 % Type 1: Orthogonal Kernel (same as type 11 below)
711 % | 1, 0, -1 |
712 % | sqrt(2), 0, -sqrt(2) | / 2*sqrt(2)
713 % | 1, 0, -1 |
714 %
715 % Type 2: Diagonal form of Kernel...
716 % | 1, sqrt(2), 0 |
717 % | sqrt(2), 0, -sqrt(2) | / 2*sqrt(2)
718 % | 0, -sqrt(2) -1 |
719 %
720 % However this kernel is als at the heart of the FreiChen Edge Detection
721 % Process which uses a set of 9 specially weighted kernel. These 9
722 % kernels not be normalized, but directly applied to the image. The
723 % results is then added together, to produce the intensity of an edge in
724 % a specific direction. The square root of the pixel value can then be
725 % taken as the cosine of the edge, and at least 2 such runs at 90 degrees
726 % from each other, both the direction and the strength of the edge can be
727 % determined.
728 %
729 % Type 10: All 9 of the following pre-weighted kernels...
730 %
731 % Type 11: | 1, 0, -1 |
732 % | sqrt(2), 0, -sqrt(2) | / 2*sqrt(2)
733 % | 1, 0, -1 |
734 %
735 % Type 12: | 1, sqrt(2), 1 |
736 % | 0, 0, 0 | / 2*sqrt(2)
737 % | 1, sqrt(2), 1 |
738 %
739 % Type 13: | sqrt(2), -1, 0 |
740 % | -1, 0, 1 | / 2*sqrt(2)
741 % | 0, 1, -sqrt(2) |
742 %
743 % Type 14: | 0, 1, -sqrt(2) |
744 % | -1, 0, 1 | / 2*sqrt(2)
745 % | sqrt(2), -1, 0 |
746 %
747 % Type 15: | 0, -1, 0 |
748 % | 1, 0, 1 | / 2
749 % | 0, -1, 0 |
750 %
751 % Type 16: | 1, 0, -1 |
752 % | 0, 0, 0 | / 2
753 % | -1, 0, 1 |
754 %
755 % Type 17: | 1, -2, 1 |
756 % | -2, 4, -2 | / 6
757 % | -1, -2, 1 |
758 %
759 % Type 18: | -2, 1, -2 |
760 % | 1, 4, 1 | / 6
761 % | -2, 1, -2 |
762 %
763 % Type 19: | 1, 1, 1 |
764 % | 1, 1, 1 | / 3
765 % | 1, 1, 1 |
766 %
767 % The first 4 are for edge detection, the next 4 are for line detection
768 % and the last is to add a average component to the results.
769 %
770 % Using a special type of '-1' will return all 9 pre-weighted kernels
771 % as a multi-kernel list, so that you can use them directly (without
772 % normalization) with the special "-set option:morphology:compose Plus"
773 % setting to apply the full FreiChen Edge Detection Technique.
774 %
775 % If 'type' is large it will be taken to be an actual rotation angle for
776 % the default FreiChen (type 0) kernel. As such FreiChen:45 will look
777 % like a Sobel:45 but with 'sqrt(2)' instead of '2' values.
778 %
779 % WARNING: The above was layed out as per
780 % http://www.math.tau.ac.il/~turkel/notes/edge_detectors.pdf
781 % But rotated 90 degrees so direction is from left rather than the top.
782 % I have yet to find any secondary confirmation of the above. The only
783 % other source found was actual source code at
784 % http://ltswww.epfl.ch/~courstiv/exos_labos/sol3.pdf
785 % Neigher paper defineds the kernels in a way that looks locical or
786 % correct when taken as a whole.
787 %
788 % Boolean Kernels
789 %
790 % Diamond:[{radius}[,{scale}]]
791 % Generate a diamond shaped kernel with given radius to the points.
792 % Kernel size will again be radius*2+1 square and defaults to radius 1,
793 % generating a 3x3 kernel that is slightly larger than a square.
794 %
795 % Square:[{radius}[,{scale}]]
796 % Generate a square shaped kernel of size radius*2+1, and defaulting
797 % to a 3x3 (radius 1).
798 %
799 % Octagon:[{radius}[,{scale}]]
800 % Generate octagonal shaped kernel of given radius and constant scale.
801 % Default radius is 3 producing a 7x7 kernel. A radius of 1 will result
802 % in "Diamond" kernel.
803 %
804 % Disk:[{radius}[,{scale}]]
805 % Generate a binary disk, thresholded at the radius given, the radius
806 % may be a float-point value. Final Kernel size is floor(radius)*2+1
807 % square. A radius of 5.3 is the default.
808 %
809 % NOTE: That a low radii Disk kernels produce the same results as
810 % many of the previously defined kernels, but differ greatly at larger
811 % radii. Here is a table of equivalences...
812 % "Disk:1" => "Diamond", "Octagon:1", or "Cross:1"
813 % "Disk:1.5" => "Square"
814 % "Disk:2" => "Diamond:2"
815 % "Disk:2.5" => "Octagon"
816 % "Disk:2.9" => "Square:2"
817 % "Disk:3.5" => "Octagon:3"
818 % "Disk:4.5" => "Octagon:4"
819 % "Disk:5.4" => "Octagon:5"
820 % "Disk:6.4" => "Octagon:6"
821 % All other Disk shapes are unique to this kernel, but because a "Disk"
822 % is more circular when using a larger radius, using a larger radius is
823 % preferred over iterating the morphological operation.
824 %
825 % Rectangle:{geometry}
826 % Simply generate a rectangle of 1's with the size given. You can also
827 % specify the location of the 'control point', otherwise the closest
828 % pixel to the center of the rectangle is selected.
829 %
830 % Properly centered and odd sized rectangles work the best.
831 %
832 % Symbol Dilation Kernels
833 %
834 % These kernel is not a good general morphological kernel, but is used
835 % more for highlighting and marking any single pixels in an image using,
836 % a "Dilate" method as appropriate.
837 %
838 % For the same reasons iterating these kernels does not produce the
839 % same result as using a larger radius for the symbol.
840 %
841 % Plus:[{radius}[,{scale}]]
842 % Cross:[{radius}[,{scale}]]
843 % Generate a kernel in the shape of a 'plus' or a 'cross' with
844 % a each arm the length of the given radius (default 2).
845 %
846 % NOTE: "plus:1" is equivalent to a "Diamond" kernel.
847 %
848 % Ring:{radius1},{radius2}[,{scale}]
849 % A ring of the values given that falls between the two radii.
850 % Defaults to a ring of approximataly 3 radius in a 7x7 kernel.
851 % This is the 'edge' pixels of the default "Disk" kernel,
852 % More specifically, "Ring" -> "Ring:2.5,3.5,1.0"
853 %
854 % Hit and Miss Kernels
855 %
856 % Peak:radius1,radius2
857 % Find any peak larger than the pixels the fall between the two radii.
858 % The default ring of pixels is as per "Ring".
859 % Edges
860 % Find flat orthogonal edges of a binary shape
861 % Corners
862 % Find 90 degree corners of a binary shape
863 % Diagonals:type
864 % A special kernel to thin the 'outside' of diagonals
865 % LineEnds:type
866 % Find end points of lines (for pruning a skeletion)
867 % Two types of lines ends (default to both) can be searched for
868 % Type 0: All line ends
869 % Type 1: single kernel for 4-conneected line ends
870 % Type 2: single kernel for simple line ends
871 % LineJunctions
872 % Find three line junctions (within a skeletion)
873 % Type 0: all line junctions
874 % Type 1: Y Junction kernel
875 % Type 2: Diagonal T Junction kernel
876 % Type 3: Orthogonal T Junction kernel
877 % Type 4: Diagonal X Junction kernel
878 % Type 5: Orthogonal + Junction kernel
879 % Ridges:type
880 % Find single pixel ridges or thin lines
881 % Type 1: Fine single pixel thick lines and ridges
882 % Type 2: Find two pixel thick lines and ridges
883 % ConvexHull
884 % Octagonal Thickening Kernel, to generate convex hulls of 45 degrees
885 % Skeleton:type
886 % Traditional skeleton generating kernels.
887 % Type 1: Tradional Skeleton kernel (4 connected skeleton)
888 % Type 2: HIPR2 Skeleton kernel (8 connected skeleton)
889 % Type 3: Thinning skeleton based on a ressearch paper by
890 % Dan S. Bloomberg (Default Type)
891 % ThinSE:type
892 % A huge variety of Thinning Kernels designed to preserve conectivity.
893 % many other kernel sets use these kernels as source definitions.
894 % Type numbers are 41-49, 81-89, 481, and 482 which are based on
895 % the super and sub notations used in the source research paper.
896 %
897 % Distance Measuring Kernels
898 %
899 % Different types of distance measuring methods, which are used with the
900 % a 'Distance' morphology method for generating a gradient based on
901 % distance from an edge of a binary shape, though there is a technique
902 % for handling a anti-aliased shape.
903 %
904 % See the 'Distance' Morphological Method, for information of how it is
905 % applied.
906 %
907 % Chebyshev:[{radius}][x{scale}[%!]]
908 % Chebyshev Distance (also known as Tchebychev or Chessboard distance)
909 % is a value of one to any neighbour, orthogonal or diagonal. One why
910 % of thinking of it is the number of squares a 'King' or 'Queen' in
911 % chess needs to traverse reach any other position on a chess board.
912 % It results in a 'square' like distance function, but one where
913 % diagonals are given a value that is closer than expected.
914 %
915 % Manhattan:[{radius}][x{scale}[%!]]
916 % Manhattan Distance (also known as Rectilinear, City Block, or the Taxi
917 % Cab distance metric), it is the distance needed when you can only
918 % travel in horizontal or vertical directions only. It is the
919 % distance a 'Rook' in chess would have to travel, and results in a
920 % diamond like distances, where diagonals are further than expected.
921 %
922 % Octagonal:[{radius}][x{scale}[%!]]
923 % An interleving of Manhatten and Chebyshev metrics producing an
924 % increasing octagonally shaped distance. Distances matches those of
925 % the "Octagon" shaped kernel of the same radius. The minimum radius
926 % and default is 2, producing a 5x5 kernel.
927 %
928 % Euclidean:[{radius}][x{scale}[%!]]
929 % Euclidean distance is the 'direct' or 'as the crow flys' distance.
930 % However by default the kernel size only has a radius of 1, which
931 % limits the distance to 'Knight' like moves, with only orthogonal and
932 % diagonal measurements being correct. As such for the default kernel
933 % you will get octagonal like distance function.
934 %
935 % However using a larger radius such as "Euclidean:4" you will get a
936 % much smoother distance gradient from the edge of the shape. Especially
937 % if the image is pre-processed to include any anti-aliasing pixels.
938 % Of course a larger kernel is slower to use, and not always needed.
939 %
940 % The first three Distance Measuring Kernels will only generate distances
941 % of exact multiples of {scale} in binary images. As such you can use a
942 % scale of 1 without loosing any information. However you also need some
943 % scaling when handling non-binary anti-aliased shapes.
944 %
945 % The "Euclidean" Distance Kernel however does generate a non-integer
946 % fractional results, and as such scaling is vital even for binary shapes.
947 %
948 */
949 
951  const GeometryInfo *args,ExceptionInfo *exception)
952 {
953  KernelInfo
954  *kernel;
955 
956  ssize_t
957  i;
958 
959  ssize_t
960  u,
961  v;
962 
963  double
964  nan = sqrt((double)-1.0); /* Special Value : Not A Number */
965 
966  /* Generate a new empty kernel if needed */
967  kernel=(KernelInfo *) NULL;
968  switch(type) {
969  case UndefinedKernel: /* These should not call this function */
970  case UserDefinedKernel:
972  "InvalidOption","`%s'","Should not call this function");
973  return((KernelInfo *) NULL);
974  case LaplacianKernel: /* Named Descrete Convolution Kernels */
975  case SobelKernel: /* these are defined using other kernels */
976  case RobertsKernel:
977  case PrewittKernel:
978  case CompassKernel:
979  case KirschKernel:
980  case FreiChenKernel:
981  case EdgesKernel: /* Hit and Miss kernels */
982  case CornersKernel:
983  case DiagonalsKernel:
984  case LineEndsKernel:
985  case LineJunctionsKernel:
986  case RidgesKernel:
987  case ConvexHullKernel:
988  case SkeletonKernel:
989  case ThinSEKernel:
990  break; /* A pre-generated kernel is not needed */
991 #if 0
992  /* set to 1 to do a compile-time check that we haven't missed anything */
993  case UnityKernel:
994  case GaussianKernel:
995  case DoGKernel:
996  case LoGKernel:
997  case BlurKernel:
998  case CometKernel:
999  case BinomialKernel:
1000  case DiamondKernel:
1001  case SquareKernel:
1002  case RectangleKernel:
1003  case OctagonKernel:
1004  case DiskKernel:
1005  case PlusKernel:
1006  case CrossKernel:
1007  case RingKernel:
1008  case PeaksKernel:
1009  case ChebyshevKernel:
1010  case ManhattanKernel:
1011  case OctangonalKernel:
1012  case EuclideanKernel:
1013 #else
1014  default:
1015 #endif
1016  /* Generate the base Kernel Structure */
1017  kernel=(KernelInfo *) AcquireMagickMemory(sizeof(*kernel));
1018  if (kernel == (KernelInfo *) NULL)
1019  return(kernel);
1020  (void) memset(kernel,0,sizeof(*kernel));
1021  kernel->minimum = kernel->maximum = kernel->angle = 0.0;
1022  kernel->negative_range = kernel->positive_range = 0.0;
1023  kernel->type = type;
1024  kernel->next = (KernelInfo *) NULL;
1026  break;
1027  }
1028 
1029  switch(type) {
1030  /*
1031  Convolution Kernels
1032  */
1033  case UnityKernel:
1034  {
1035  kernel->height = kernel->width = (size_t) 1;
1036  kernel->x = kernel->y = (ssize_t) 0;
1038  AcquireAlignedMemory(1,sizeof(*kernel->values)));
1039  if (kernel->values == (MagickRealType *) NULL)
1040  return(DestroyKernelInfo(kernel));
1041  kernel->maximum = kernel->values[0] = args->rho;
1042  break;
1043  }
1044  break;
1045  case GaussianKernel:
1046  case DoGKernel:
1047  case LoGKernel:
1048  { double
1049  sigma = fabs(args->sigma),
1050  sigma2 = fabs(args->xi),
1051  A, B, R;
1052 
1053  if ( args->rho >= 1.0 )
1054  kernel->width = (size_t)args->rho*2+1;
1055  else if ( (type != DoGKernel) || (sigma >= sigma2) )
1056  kernel->width = GetOptimalKernelWidth2D(args->rho,sigma);
1057  else
1058  kernel->width = GetOptimalKernelWidth2D(args->rho,sigma2);
1059  kernel->height = kernel->width;
1060  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1062  AcquireAlignedMemory(kernel->width,kernel->height*
1063  sizeof(*kernel->values)));
1064  if (kernel->values == (MagickRealType *) NULL)
1065  return(DestroyKernelInfo(kernel));
1066 
1067  /* WARNING: The following generates a 'sampled gaussian' kernel.
1068  * What we really want is a 'discrete gaussian' kernel.
1069  *
1070  * How to do this is I don't know, but appears to be basied on the
1071  * Error Function 'erf()' (intergral of a gaussian)
1072  */
1073 
1074  if ( type == GaussianKernel || type == DoGKernel )
1075  { /* Calculate a Gaussian, OR positive half of a DoG */
1076  if ( sigma > MagickEpsilon )
1077  { A = 1.0/(2.0*sigma*sigma); /* simplify loop expressions */
1078  B = (double) (1.0/(Magick2PI*sigma*sigma));
1079  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1080  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1081  kernel->values[i] = exp(-((double)(u*u+v*v))*A)*B;
1082  }
1083  else /* limiting case - a unity (normalized Dirac) kernel */
1084  { (void) memset(kernel->values,0, (size_t)
1085  kernel->width*kernel->height*sizeof(*kernel->values));
1086  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1087  }
1088  }
1089 
1090  if ( type == DoGKernel )
1091  { /* Subtract a Negative Gaussian for "Difference of Gaussian" */
1092  if ( sigma2 > MagickEpsilon )
1093  { sigma = sigma2; /* simplify loop expressions */
1094  A = 1.0/(2.0*sigma*sigma);
1095  B = (double) (1.0/(Magick2PI*sigma*sigma));
1096  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1097  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1098  kernel->values[i] -= exp(-((double)(u*u+v*v))*A)*B;
1099  }
1100  else /* limiting case - a unity (normalized Dirac) kernel */
1101  kernel->values[kernel->x+kernel->y*kernel->width] -= 1.0;
1102  }
1103 
1104  if ( type == LoGKernel )
1105  { /* Calculate a Laplacian of a Gaussian - Or Mexician Hat */
1106  if ( sigma > MagickEpsilon )
1107  { A = 1.0/(2.0*sigma*sigma); /* simplify loop expressions */
1108  B = (double) (1.0/(MagickPI*sigma*sigma*sigma*sigma));
1109  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1110  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1111  { R = ((double)(u*u+v*v))*A;
1112  kernel->values[i] = (1-R)*exp(-R)*B;
1113  }
1114  }
1115  else /* special case - generate a unity kernel */
1116  { (void) memset(kernel->values,0, (size_t)
1117  kernel->width*kernel->height*sizeof(*kernel->values));
1118  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1119  }
1120  }
1121 
1122  /* Note the above kernels may have been 'clipped' by a user defined
1123  ** radius, producing a smaller (darker) kernel. Also for very small
1124  ** sigma's (> 0.1) the central value becomes larger than one, and thus
1125  ** producing a very bright kernel.
1126  **
1127  ** Normalization will still be needed.
1128  */
1129 
1130  /* Normalize the 2D Gaussian Kernel
1131  **
1132  ** NB: a CorrelateNormalize performs a normal Normalize if
1133  ** there are no negative values.
1134  */
1135  CalcKernelMetaData(kernel); /* the other kernel meta-data */
1137 
1138  break;
1139  }
1140  case BlurKernel:
1141  { double
1142  sigma = fabs(args->sigma),
1143  alpha, beta;
1144 
1145  if ( args->rho >= 1.0 )
1146  kernel->width = (size_t)args->rho*2+1;
1147  else
1148  kernel->width = GetOptimalKernelWidth1D(args->rho,sigma);
1149  kernel->height = 1;
1150  kernel->x = (ssize_t) (kernel->width-1)/2;
1151  kernel->y = 0;
1152  kernel->negative_range = kernel->positive_range = 0.0;
1154  AcquireAlignedMemory(kernel->width,kernel->height*
1155  sizeof(*kernel->values)));
1156  if (kernel->values == (MagickRealType *) NULL)
1157  return(DestroyKernelInfo(kernel));
1158 
1159 #if 1
1160 #define KernelRank 3
1161  /* Formula derived from GetBlurKernel() in "effect.c" (plus bug fix).
1162  ** It generates a gaussian 3 times the width, and compresses it into
1163  ** the expected range. This produces a closer normalization of the
1164  ** resulting kernel, especially for very low sigma values.
1165  ** As such while wierd it is prefered.
1166  **
1167  ** I am told this method originally came from Photoshop.
1168  **
1169  ** A properly normalized curve is generated (apart from edge clipping)
1170  ** even though we later normalize the result (for edge clipping)
1171  ** to allow the correct generation of a "Difference of Blurs".
1172  */
1173 
1174  /* initialize */
1175  v = (ssize_t) (kernel->width*KernelRank-1)/2; /* start/end points to fit range */
1176  (void) memset(kernel->values,0, (size_t)
1177  kernel->width*kernel->height*sizeof(*kernel->values));
1178  /* Calculate a Positive 1D Gaussian */
1179  if ( sigma > MagickEpsilon )
1180  { sigma *= KernelRank; /* simplify loop expressions */
1181  alpha = 1.0/(2.0*sigma*sigma);
1182  beta= (double) (1.0/(MagickSQ2PI*sigma ));
1183  for ( u=-v; u <= v; u++) {
1184  kernel->values[(u+v)/KernelRank] +=
1185  exp(-((double)(u*u))*alpha)*beta;
1186  }
1187  }
1188  else /* special case - generate a unity kernel */
1189  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1190 #else
1191  /* Direct calculation without curve averaging
1192  This is equivelent to a KernelRank of 1 */
1193 
1194  /* Calculate a Positive Gaussian */
1195  if ( sigma > MagickEpsilon )
1196  { alpha = 1.0/(2.0*sigma*sigma); /* simplify loop expressions */
1197  beta = 1.0/(MagickSQ2PI*sigma);
1198  for ( i=0, u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1199  kernel->values[i] = exp(-((double)(u*u))*alpha)*beta;
1200  }
1201  else /* special case - generate a unity kernel */
1202  { (void) memset(kernel->values,0, (size_t)
1203  kernel->width*kernel->height*sizeof(*kernel->values));
1204  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1205  }
1206 #endif
1207  /* Note the above kernel may have been 'clipped' by a user defined
1208  ** radius, producing a smaller (darker) kernel. Also for very small
1209  ** sigma's (> 0.1) the central value becomes larger than one, as a
1210  ** result of not generating a actual 'discrete' kernel, and thus
1211  ** producing a very bright 'impulse'.
1212  **
1213  ** Becuase of these two factors Normalization is required!
1214  */
1215 
1216  /* Normalize the 1D Gaussian Kernel
1217  **
1218  ** NB: a CorrelateNormalize performs a normal Normalize if
1219  ** there are no negative values.
1220  */
1221  CalcKernelMetaData(kernel); /* the other kernel meta-data */
1223 
1224  /* rotate the 1D kernel by given angle */
1225  RotateKernelInfo(kernel, args->xi );
1226  break;
1227  }
1228  case CometKernel:
1229  { double
1230  sigma = fabs(args->sigma),
1231  A;
1232 
1233  if ( args->rho < 1.0 )
1234  kernel->width = (GetOptimalKernelWidth1D(args->rho,sigma)-1)/2+1;
1235  else
1236  kernel->width = (size_t)args->rho;
1237  kernel->x = kernel->y = 0;
1238  kernel->height = 1;
1239  kernel->negative_range = kernel->positive_range = 0.0;
1241  AcquireAlignedMemory(kernel->width,kernel->height*
1242  sizeof(*kernel->values)));
1243  if (kernel->values == (MagickRealType *) NULL)
1244  return(DestroyKernelInfo(kernel));
1245 
1246  /* A comet blur is half a 1D gaussian curve, so that the object is
1247  ** blurred in one direction only. This may not be quite the right
1248  ** curve to use so may change in the future. The function must be
1249  ** normalised after generation, which also resolves any clipping.
1250  **
1251  ** As we are normalizing and not subtracting gaussians,
1252  ** there is no need for a divisor in the gaussian formula
1253  **
1254  ** It is less comples
1255  */
1256  if ( sigma > MagickEpsilon )
1257  {
1258 #if 1
1259 #define KernelRank 3
1260  v = (ssize_t) kernel->width*KernelRank; /* start/end points */
1261  (void) memset(kernel->values,0, (size_t)
1262  kernel->width*sizeof(*kernel->values));
1263  sigma *= KernelRank; /* simplify the loop expression */
1264  A = 1.0/(2.0*sigma*sigma);
1265  /* B = 1.0/(MagickSQ2PI*sigma); */
1266  for ( u=0; u < v; u++) {
1267  kernel->values[u/KernelRank] +=
1268  exp(-((double)(u*u))*A);
1269  /* exp(-((double)(i*i))/2.0*sigma*sigma)/(MagickSQ2PI*sigma); */
1270  }
1271  for (i=0; i < (ssize_t) kernel->width; i++)
1272  kernel->positive_range += kernel->values[i];
1273 #else
1274  A = 1.0/(2.0*sigma*sigma); /* simplify the loop expression */
1275  /* B = 1.0/(MagickSQ2PI*sigma); */
1276  for ( i=0; i < (ssize_t) kernel->width; i++)
1277  kernel->positive_range +=
1278  kernel->values[i] = exp(-((double)(i*i))*A);
1279  /* exp(-((double)(i*i))/2.0*sigma*sigma)/(MagickSQ2PI*sigma); */
1280 #endif
1281  }
1282  else /* special case - generate a unity kernel */
1283  { (void) memset(kernel->values,0, (size_t)
1284  kernel->width*kernel->height*sizeof(*kernel->values));
1285  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1286  kernel->positive_range = 1.0;
1287  }
1288 
1289  kernel->minimum = 0.0;
1290  kernel->maximum = kernel->values[0];
1291  kernel->negative_range = 0.0;
1292 
1293  ScaleKernelInfo(kernel, 1.0, NormalizeValue); /* Normalize */
1294  RotateKernelInfo(kernel, args->xi); /* Rotate by angle */
1295  break;
1296  }
1297  case BinomialKernel:
1298  {
1299  size_t
1300  order_f;
1301 
1302  if (args->rho < 1.0)
1303  kernel->width = kernel->height = 3; /* default radius = 1 */
1304  else
1305  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1306  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1307 
1308  order_f = fact(kernel->width-1);
1309 
1311  AcquireAlignedMemory(kernel->width,kernel->height*
1312  sizeof(*kernel->values)));
1313  if (kernel->values == (MagickRealType *) NULL)
1314  return(DestroyKernelInfo(kernel));
1315 
1316  /* set all kernel values within diamond area to scale given */
1317  for ( i=0, v=0; v < (ssize_t)kernel->height; v++)
1318  { size_t
1319  alpha = order_f / ( fact((size_t) v) * fact(kernel->height-v-1) );
1320  for ( u=0; u < (ssize_t)kernel->width; u++, i++)
1321  kernel->positive_range += kernel->values[i] = (double)
1322  (alpha * order_f / ( fact((size_t) u) * fact(kernel->height-u-1) ));
1323  }
1324  kernel->minimum = 1.0;
1325  kernel->maximum = kernel->values[kernel->x+kernel->y*kernel->width];
1326  kernel->negative_range = 0.0;
1327  break;
1328  }
1329 
1330  /*
1331  Convolution Kernels - Well Known Named Constant Kernels
1332  */
1333  case LaplacianKernel:
1334  { switch ( (int) args->rho ) {
1335  case 0:
1336  default: /* laplacian square filter -- default */
1337  kernel=ParseKernelArray("3: -1,-1,-1 -1,8,-1 -1,-1,-1");
1338  break;
1339  case 1: /* laplacian diamond filter */
1340  kernel=ParseKernelArray("3: 0,-1,0 -1,4,-1 0,-1,0");
1341  break;
1342  case 2:
1343  kernel=ParseKernelArray("3: -2,1,-2 1,4,1 -2,1,-2");
1344  break;
1345  case 3:
1346  kernel=ParseKernelArray("3: 1,-2,1 -2,4,-2 1,-2,1");
1347  break;
1348  case 5: /* a 5x5 laplacian */
1349  kernel=ParseKernelArray(
1350  "5: -4,-1,0,-1,-4 -1,2,3,2,-1 0,3,4,3,0 -1,2,3,2,-1 -4,-1,0,-1,-4");
1351  break;
1352  case 7: /* a 7x7 laplacian */
1353  kernel=ParseKernelArray(
1354  "7:-10,-5,-2,-1,-2,-5,-10 -5,0,3,4,3,0,-5 -2,3,6,7,6,3,-2 -1,4,7,8,7,4,-1 -2,3,6,7,6,3,-2 -5,0,3,4,3,0,-5 -10,-5,-2,-1,-2,-5,-10" );
1355  break;
1356  case 15: /* a 5x5 LoG (sigma approx 1.4) */
1357  kernel=ParseKernelArray(
1358  "5: 0,0,-1,0,0 0,-1,-2,-1,0 -1,-2,16,-2,-1 0,-1,-2,-1,0 0,0,-1,0,0");
1359  break;
1360  case 19: /* a 9x9 LoG (sigma approx 1.4) */
1361  /* http://www.cscjournals.org/csc/manuscript/Journals/IJIP/volume3/Issue1/IJIP-15.pdf */
1362  kernel=ParseKernelArray(
1363  "9: 0,-1,-1,-2,-2,-2,-1,-1,0 -1,-2,-4,-5,-5,-5,-4,-2,-1 -1,-4,-5,-3,-0,-3,-5,-4,-1 -2,-5,-3,12,24,12,-3,-5,-2 -2,-5,-0,24,40,24,-0,-5,-2 -2,-5,-3,12,24,12,-3,-5,-2 -1,-4,-5,-3,-0,-3,-5,-4,-1 -1,-2,-4,-5,-5,-5,-4,-2,-1 0,-1,-1,-2,-2,-2,-1,-1,0");
1364  break;
1365  }
1366  if (kernel == (KernelInfo *) NULL)
1367  return(kernel);
1368  kernel->type = type;
1369  break;
1370  }
1371  case SobelKernel:
1372  { /* Simple Sobel Kernel */
1373  kernel=ParseKernelArray("3: 1,0,-1 2,0,-2 1,0,-1");
1374  if (kernel == (KernelInfo *) NULL)
1375  return(kernel);
1376  kernel->type = type;
1377  RotateKernelInfo(kernel, args->rho);
1378  break;
1379  }
1380  case RobertsKernel:
1381  {
1382  kernel=ParseKernelArray("3: 0,0,0 1,-1,0 0,0,0");
1383  if (kernel == (KernelInfo *) NULL)
1384  return(kernel);
1385  kernel->type = type;
1386  RotateKernelInfo(kernel, args->rho);
1387  break;
1388  }
1389  case PrewittKernel:
1390  {
1391  kernel=ParseKernelArray("3: 1,0,-1 1,0,-1 1,0,-1");
1392  if (kernel == (KernelInfo *) NULL)
1393  return(kernel);
1394  kernel->type = type;
1395  RotateKernelInfo(kernel, args->rho);
1396  break;
1397  }
1398  case CompassKernel:
1399  {
1400  kernel=ParseKernelArray("3: 1,1,-1 1,-2,-1 1,1,-1");
1401  if (kernel == (KernelInfo *) NULL)
1402  return(kernel);
1403  kernel->type = type;
1404  RotateKernelInfo(kernel, args->rho);
1405  break;
1406  }
1407  case KirschKernel:
1408  {
1409  kernel=ParseKernelArray("3: 5,-3,-3 5,0,-3 5,-3,-3");
1410  if (kernel == (KernelInfo *) NULL)
1411  return(kernel);
1412  kernel->type = type;
1413  RotateKernelInfo(kernel, args->rho);
1414  break;
1415  }
1416  case FreiChenKernel:
1417  /* Direction is set to be left to right positive */
1418  /* http://www.math.tau.ac.il/~turkel/notes/edge_detectors.pdf -- RIGHT? */
1419  /* http://ltswww.epfl.ch/~courstiv/exos_labos/sol3.pdf -- WRONG? */
1420  { switch ( (int) args->rho ) {
1421  default:
1422  case 0:
1423  kernel=ParseKernelArray("3: 1,0,-1 2,0,-2 1,0,-1");
1424  if (kernel == (KernelInfo *) NULL)
1425  return(kernel);
1426  kernel->type = type;
1427  kernel->values[3] = +(MagickRealType) MagickSQ2;
1428  kernel->values[5] = -(MagickRealType) MagickSQ2;
1429  CalcKernelMetaData(kernel); /* recalculate meta-data */
1430  break;
1431  case 2:
1432  kernel=ParseKernelArray("3: 1,2,0 2,0,-2 0,-2,-1");
1433  if (kernel == (KernelInfo *) NULL)
1434  return(kernel);
1435  kernel->type = type;
1436  kernel->values[1] = kernel->values[3]= +(MagickRealType) MagickSQ2;
1437  kernel->values[5] = kernel->values[7]= -(MagickRealType) MagickSQ2;
1438  CalcKernelMetaData(kernel); /* recalculate meta-data */
1439  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1440  break;
1441  case 10:
1442  {
1443  kernel=AcquireKernelInfo("FreiChen:11;FreiChen:12;FreiChen:13;FreiChen:14;FreiChen:15;FreiChen:16;FreiChen:17;FreiChen:18;FreiChen:19",exception);
1444  if (kernel == (KernelInfo *) NULL)
1445  return(kernel);
1446  break;
1447  }
1448  case 1:
1449  case 11:
1450  kernel=ParseKernelArray("3: 1,0,-1 2,0,-2 1,0,-1");
1451  if (kernel == (KernelInfo *) NULL)
1452  return(kernel);
1453  kernel->type = type;
1454  kernel->values[3] = +(MagickRealType) MagickSQ2;
1455  kernel->values[5] = -(MagickRealType) MagickSQ2;
1456  CalcKernelMetaData(kernel); /* recalculate meta-data */
1457  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1458  break;
1459  case 12:
1460  kernel=ParseKernelArray("3: 1,2,1 0,0,0 1,2,1");
1461  if (kernel == (KernelInfo *) NULL)
1462  return(kernel);
1463  kernel->type = type;
1464  kernel->values[1] = +(MagickRealType) MagickSQ2;
1465  kernel->values[7] = +(MagickRealType) MagickSQ2;
1466  CalcKernelMetaData(kernel);
1467  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1468  break;
1469  case 13:
1470  kernel=ParseKernelArray("3: 2,-1,0 -1,0,1 0,1,-2");
1471  if (kernel == (KernelInfo *) NULL)
1472  return(kernel);
1473  kernel->type = type;
1474  kernel->values[0] = +(MagickRealType) MagickSQ2;
1475  kernel->values[8] = -(MagickRealType) MagickSQ2;
1476  CalcKernelMetaData(kernel);
1477  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1478  break;
1479  case 14:
1480  kernel=ParseKernelArray("3: 0,1,-2 -1,0,1 2,-1,0");
1481  if (kernel == (KernelInfo *) NULL)
1482  return(kernel);
1483  kernel->type = type;
1484  kernel->values[2] = -(MagickRealType) MagickSQ2;
1485  kernel->values[6] = +(MagickRealType) MagickSQ2;
1486  CalcKernelMetaData(kernel);
1487  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1488  break;
1489  case 15:
1490  kernel=ParseKernelArray("3: 0,-1,0 1,0,1 0,-1,0");
1491  if (kernel == (KernelInfo *) NULL)
1492  return(kernel);
1493  kernel->type = type;
1494  ScaleKernelInfo(kernel, 1.0/2.0, NoValue);
1495  break;
1496  case 16:
1497  kernel=ParseKernelArray("3: 1,0,-1 0,0,0 -1,0,1");
1498  if (kernel == (KernelInfo *) NULL)
1499  return(kernel);
1500  kernel->type = type;
1501  ScaleKernelInfo(kernel, 1.0/2.0, NoValue);
1502  break;
1503  case 17:
1504  kernel=ParseKernelArray("3: 1,-2,1 -2,4,-2 -1,-2,1");
1505  if (kernel == (KernelInfo *) NULL)
1506  return(kernel);
1507  kernel->type = type;
1508  ScaleKernelInfo(kernel, 1.0/6.0, NoValue);
1509  break;
1510  case 18:
1511  kernel=ParseKernelArray("3: -2,1,-2 1,4,1 -2,1,-2");
1512  if (kernel == (KernelInfo *) NULL)
1513  return(kernel);
1514  kernel->type = type;
1515  ScaleKernelInfo(kernel, 1.0/6.0, NoValue);
1516  break;
1517  case 19:
1518  kernel=ParseKernelArray("3: 1,1,1 1,1,1 1,1,1");
1519  if (kernel == (KernelInfo *) NULL)
1520  return(kernel);
1521  kernel->type = type;
1522  ScaleKernelInfo(kernel, 1.0/3.0, NoValue);
1523  break;
1524  }
1525  if ( fabs(args->sigma) >= MagickEpsilon )
1526  /* Rotate by correctly supplied 'angle' */
1527  RotateKernelInfo(kernel, args->sigma);
1528  else if ( args->rho > 30.0 || args->rho < -30.0 )
1529  /* Rotate by out of bounds 'type' */
1530  RotateKernelInfo(kernel, args->rho);
1531  break;
1532  }
1533 
1534  /*
1535  Boolean or Shaped Kernels
1536  */
1537  case DiamondKernel:
1538  {
1539  if (args->rho < 1.0)
1540  kernel->width = kernel->height = 3; /* default radius = 1 */
1541  else
1542  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1543  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1544 
1546  AcquireAlignedMemory(kernel->width,kernel->height*
1547  sizeof(*kernel->values)));
1548  if (kernel->values == (MagickRealType *) NULL)
1549  return(DestroyKernelInfo(kernel));
1550 
1551  /* set all kernel values within diamond area to scale given */
1552  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1553  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1554  if ( (labs((long) u)+labs((long) v)) <= (long) kernel->x)
1555  kernel->positive_range += kernel->values[i] = args->sigma;
1556  else
1557  kernel->values[i] = nan;
1558  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1559  break;
1560  }
1561  case SquareKernel:
1562  case RectangleKernel:
1563  { double
1564  scale;
1565  if ( type == SquareKernel )
1566  {
1567  if (args->rho < 1.0)
1568  kernel->width = kernel->height = 3; /* default radius = 1 */
1569  else
1570  kernel->width = kernel->height = (size_t) (2*args->rho+1);
1571  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1572  scale = args->sigma;
1573  }
1574  else {
1575  /* NOTE: user defaults set in "AcquireKernelInfo()" */
1576  if ( args->rho < 1.0 || args->sigma < 1.0 )
1577  return(DestroyKernelInfo(kernel)); /* invalid args given */
1578  kernel->width = (size_t)args->rho;
1579  kernel->height = (size_t)args->sigma;
1580  if ( args->xi < 0.0 || args->xi > (double)kernel->width ||
1581  args->psi < 0.0 || args->psi > (double)kernel->height )
1582  return(DestroyKernelInfo(kernel)); /* invalid args given */
1583  kernel->x = (ssize_t) args->xi;
1584  kernel->y = (ssize_t) args->psi;
1585  scale = 1.0;
1586  }
1588  AcquireAlignedMemory(kernel->width,kernel->height*
1589  sizeof(*kernel->values)));
1590  if (kernel->values == (MagickRealType *) NULL)
1591  return(DestroyKernelInfo(kernel));
1592 
1593  /* set all kernel values to scale given */
1594  u=(ssize_t) (kernel->width*kernel->height);
1595  for ( i=0; i < u; i++)
1596  kernel->values[i] = scale;
1597  kernel->minimum = kernel->maximum = scale; /* a flat shape */
1598  kernel->positive_range = scale*u;
1599  break;
1600  }
1601  case OctagonKernel:
1602  {
1603  if (args->rho < 1.0)
1604  kernel->width = kernel->height = 5; /* default radius = 2 */
1605  else
1606  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1607  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1608 
1610  AcquireAlignedMemory(kernel->width,kernel->height*
1611  sizeof(*kernel->values)));
1612  if (kernel->values == (MagickRealType *) NULL)
1613  return(DestroyKernelInfo(kernel));
1614 
1615  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1616  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1617  if ( (labs((long) u)+labs((long) v)) <=
1618  ((long)kernel->x + (long)(kernel->x/2)) )
1619  kernel->positive_range += kernel->values[i] = args->sigma;
1620  else
1621  kernel->values[i] = nan;
1622  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1623  break;
1624  }
1625  case DiskKernel:
1626  {
1627  ssize_t
1628  limit = (ssize_t)(args->rho*args->rho);
1629 
1630  if (args->rho < 0.4) /* default radius approx 4.3 */
1631  kernel->width = kernel->height = 9L, limit = 18L;
1632  else
1633  kernel->width = kernel->height = (size_t)fabs(args->rho)*2+1;
1634  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1635 
1637  AcquireAlignedMemory(kernel->width,kernel->height*
1638  sizeof(*kernel->values)));
1639  if (kernel->values == (MagickRealType *) NULL)
1640  return(DestroyKernelInfo(kernel));
1641 
1642  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1643  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1644  if ((u*u+v*v) <= limit)
1645  kernel->positive_range += kernel->values[i] = args->sigma;
1646  else
1647  kernel->values[i] = nan;
1648  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1649  break;
1650  }
1651  case PlusKernel:
1652  {
1653  if (args->rho < 1.0)
1654  kernel->width = kernel->height = 5; /* default radius 2 */
1655  else
1656  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1657  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1658 
1660  AcquireAlignedMemory(kernel->width,kernel->height*
1661  sizeof(*kernel->values)));
1662  if (kernel->values == (MagickRealType *) NULL)
1663  return(DestroyKernelInfo(kernel));
1664 
1665  /* set all kernel values along axises to given scale */
1666  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1667  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1668  kernel->values[i] = (u == 0 || v == 0) ? args->sigma : nan;
1669  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1670  kernel->positive_range = args->sigma*(kernel->width*2.0 - 1.0);
1671  break;
1672  }
1673  case CrossKernel:
1674  {
1675  if (args->rho < 1.0)
1676  kernel->width = kernel->height = 5; /* default radius 2 */
1677  else
1678  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1679  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1680 
1682  AcquireAlignedMemory(kernel->width,kernel->height*
1683  sizeof(*kernel->values)));
1684  if (kernel->values == (MagickRealType *) NULL)
1685  return(DestroyKernelInfo(kernel));
1686 
1687  /* set all kernel values along axises to given scale */
1688  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1689  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1690  kernel->values[i] = (u == v || u == -v) ? args->sigma : nan;
1691  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1692  kernel->positive_range = args->sigma*(kernel->width*2.0 - 1.0);
1693  break;
1694  }
1695  /*
1696  HitAndMiss Kernels
1697  */
1698  case RingKernel:
1699  case PeaksKernel:
1700  {
1701  ssize_t
1702  limit1,
1703  limit2,
1704  scale;
1705 
1706  if (args->rho < args->sigma)
1707  {
1708  kernel->width = ((size_t)args->sigma)*2+1;
1709  limit1 = (ssize_t)(args->rho*args->rho);
1710  limit2 = (ssize_t)(args->sigma*args->sigma);
1711  }
1712  else
1713  {
1714  kernel->width = ((size_t)args->rho)*2+1;
1715  limit1 = (ssize_t)(args->sigma*args->sigma);
1716  limit2 = (ssize_t)(args->rho*args->rho);
1717  }
1718  if ( limit2 <= 0 )
1719  kernel->width = 7L, limit1 = 7L, limit2 = 11L;
1720 
1721  kernel->height = kernel->width;
1722  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1724  AcquireAlignedMemory(kernel->width,kernel->height*
1725  sizeof(*kernel->values)));
1726  if (kernel->values == (MagickRealType *) NULL)
1727  return(DestroyKernelInfo(kernel));
1728 
1729  /* set a ring of points of 'scale' ( 0.0 for PeaksKernel ) */
1730  scale = (ssize_t) (( type == PeaksKernel) ? 0.0 : args->xi);
1731  for ( i=0, v= -kernel->y; v <= (ssize_t)kernel->y; v++)
1732  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1733  { ssize_t radius=u*u+v*v;
1734  if (limit1 < radius && radius <= limit2)
1735  kernel->positive_range += kernel->values[i] = (double) scale;
1736  else
1737  kernel->values[i] = nan;
1738  }
1739  kernel->minimum = kernel->maximum = (double) scale;
1740  if ( type == PeaksKernel ) {
1741  /* set the central point in the middle */
1742  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1743  kernel->positive_range = 1.0;
1744  kernel->maximum = 1.0;
1745  }
1746  break;
1747  }
1748  case EdgesKernel:
1749  {
1750  kernel=AcquireKernelInfo("ThinSE:482",exception);
1751  if (kernel == (KernelInfo *) NULL)
1752  return(kernel);
1753  kernel->type = type;
1754  ExpandMirrorKernelInfo(kernel); /* mirror expansion of kernels */
1755  break;
1756  }
1757  case CornersKernel:
1758  {
1759  kernel=AcquireKernelInfo("ThinSE:87",exception);
1760  if (kernel == (KernelInfo *) NULL)
1761  return(kernel);
1762  kernel->type = type;
1763  ExpandRotateKernelInfo(kernel, 90.0); /* Expand 90 degree rotations */
1764  break;
1765  }
1766  case DiagonalsKernel:
1767  {
1768  switch ( (int) args->rho ) {
1769  case 0:
1770  default:
1771  { KernelInfo
1772  *new_kernel;
1773  kernel=ParseKernelArray("3: 0,0,0 0,-,1 1,1,-");
1774  if (kernel == (KernelInfo *) NULL)
1775  return(kernel);
1776  kernel->type = type;
1777  new_kernel=ParseKernelArray("3: 0,0,1 0,-,1 0,1,-");
1778  if (new_kernel == (KernelInfo *) NULL)
1779  return(DestroyKernelInfo(kernel));
1780  new_kernel->type = type;
1781  LastKernelInfo(kernel)->next = new_kernel;
1782  ExpandMirrorKernelInfo(kernel);
1783  return(kernel);
1784  }
1785  case 1:
1786  kernel=ParseKernelArray("3: 0,0,0 0,-,1 1,1,-");
1787  break;
1788  case 2:
1789  kernel=ParseKernelArray("3: 0,0,1 0,-,1 0,1,-");
1790  break;
1791  }
1792  if (kernel == (KernelInfo *) NULL)
1793  return(kernel);
1794  kernel->type = type;
1795  RotateKernelInfo(kernel, args->sigma);
1796  break;
1797  }
1798  case LineEndsKernel:
1799  { /* Kernels for finding the end of thin lines */
1800  switch ( (int) args->rho ) {
1801  case 0:
1802  default:
1803  /* set of kernels to find all end of lines */
1804  return(AcquireKernelInfo("LineEnds:1>;LineEnds:2>",exception));
1805  case 1:
1806  /* kernel for 4-connected line ends - no rotation */
1807  kernel=ParseKernelArray("3: 0,0,- 0,1,1 0,0,-");
1808  break;
1809  case 2:
1810  /* kernel to add for 8-connected lines - no rotation */
1811  kernel=ParseKernelArray("3: 0,0,0 0,1,0 0,0,1");
1812  break;
1813  case 3:
1814  /* kernel to add for orthogonal line ends - does not find corners */
1815  kernel=ParseKernelArray("3: 0,0,0 0,1,1 0,0,0");
1816  break;
1817  case 4:
1818  /* traditional line end - fails on last T end */
1819  kernel=ParseKernelArray("3: 0,0,0 0,1,- 0,0,-");
1820  break;
1821  }
1822  if (kernel == (KernelInfo *) NULL)
1823  return(kernel);
1824  kernel->type = type;
1825  RotateKernelInfo(kernel, args->sigma);
1826  break;
1827  }
1828  case LineJunctionsKernel:
1829  { /* kernels for finding the junctions of multiple lines */
1830  switch ( (int) args->rho ) {
1831  case 0:
1832  default:
1833  /* set of kernels to find all line junctions */
1834  return(AcquireKernelInfo("LineJunctions:1@;LineJunctions:2>",exception));
1835  case 1:
1836  /* Y Junction */
1837  kernel=ParseKernelArray("3: 1,-,1 -,1,- -,1,-");
1838  break;
1839  case 2:
1840  /* Diagonal T Junctions */
1841  kernel=ParseKernelArray("3: 1,-,- -,1,- 1,-,1");
1842  break;
1843  case 3:
1844  /* Orthogonal T Junctions */
1845  kernel=ParseKernelArray("3: -,-,- 1,1,1 -,1,-");
1846  break;
1847  case 4:
1848  /* Diagonal X Junctions */
1849  kernel=ParseKernelArray("3: 1,-,1 -,1,- 1,-,1");
1850  break;
1851  case 5:
1852  /* Orthogonal X Junctions - minimal diamond kernel */
1853  kernel=ParseKernelArray("3: -,1,- 1,1,1 -,1,-");
1854  break;
1855  }
1856  if (kernel == (KernelInfo *) NULL)
1857  return(kernel);
1858  kernel->type = type;
1859  RotateKernelInfo(kernel, args->sigma);
1860  break;
1861  }
1862  case RidgesKernel:
1863  { /* Ridges - Ridge finding kernels */
1864  KernelInfo
1865  *new_kernel;
1866  switch ( (int) args->rho ) {
1867  case 1:
1868  default:
1869  kernel=ParseKernelArray("3x1:0,1,0");
1870  if (kernel == (KernelInfo *) NULL)
1871  return(kernel);
1872  kernel->type = type;
1873  ExpandRotateKernelInfo(kernel, 90.0); /* 2 rotated kernels (symmetrical) */
1874  break;
1875  case 2:
1876  kernel=ParseKernelArray("4x1:0,1,1,0");
1877  if (kernel == (KernelInfo *) NULL)
1878  return(kernel);
1879  kernel->type = type;
1880  ExpandRotateKernelInfo(kernel, 90.0); /* 4 rotated kernels */
1881 
1882  /* Kernels to find a stepped 'thick' line, 4 rotates + mirrors */
1883  /* Unfortunatally we can not yet rotate a non-square kernel */
1884  /* But then we can't flip a non-symetrical kernel either */
1885  new_kernel=ParseKernelArray("4x3+1+1:0,1,1,- -,1,1,- -,1,1,0");
1886  if (new_kernel == (KernelInfo *) NULL)
1887  return(DestroyKernelInfo(kernel));
1888  new_kernel->type = type;
1889  LastKernelInfo(kernel)->next = new_kernel;
1890  new_kernel=ParseKernelArray("4x3+2+1:0,1,1,- -,1,1,- -,1,1,0");
1891  if (new_kernel == (KernelInfo *) NULL)
1892  return(DestroyKernelInfo(kernel));
1893  new_kernel->type = type;
1894  LastKernelInfo(kernel)->next = new_kernel;
1895  new_kernel=ParseKernelArray("4x3+1+1:-,1,1,0 -,1,1,- 0,1,1,-");
1896  if (new_kernel == (KernelInfo *) NULL)
1897  return(DestroyKernelInfo(kernel));
1898  new_kernel->type = type;
1899  LastKernelInfo(kernel)->next = new_kernel;
1900  new_kernel=ParseKernelArray("4x3+2+1:-,1,1,0 -,1,1,- 0,1,1,-");
1901  if (new_kernel == (KernelInfo *) NULL)
1902  return(DestroyKernelInfo(kernel));
1903  new_kernel->type = type;
1904  LastKernelInfo(kernel)->next = new_kernel;
1905  new_kernel=ParseKernelArray("3x4+1+1:0,-,- 1,1,1 1,1,1 -,-,0");
1906  if (new_kernel == (KernelInfo *) NULL)
1907  return(DestroyKernelInfo(kernel));
1908  new_kernel->type = type;
1909  LastKernelInfo(kernel)->next = new_kernel;
1910  new_kernel=ParseKernelArray("3x4+1+2:0,-,- 1,1,1 1,1,1 -,-,0");
1911  if (new_kernel == (KernelInfo *) NULL)
1912  return(DestroyKernelInfo(kernel));
1913  new_kernel->type = type;
1914  LastKernelInfo(kernel)->next = new_kernel;
1915  new_kernel=ParseKernelArray("3x4+1+1:-,-,0 1,1,1 1,1,1 0,-,-");
1916  if (new_kernel == (KernelInfo *) NULL)
1917  return(DestroyKernelInfo(kernel));
1918  new_kernel->type = type;
1919  LastKernelInfo(kernel)->next = new_kernel;
1920  new_kernel=ParseKernelArray("3x4+1+2:-,-,0 1,1,1 1,1,1 0,-,-");
1921  if (new_kernel == (KernelInfo *) NULL)
1922  return(DestroyKernelInfo(kernel));
1923  new_kernel->type = type;
1924  LastKernelInfo(kernel)->next = new_kernel;
1925  break;
1926  }
1927  break;
1928  }
1929  case ConvexHullKernel:
1930  {
1931  KernelInfo
1932  *new_kernel;
1933  /* first set of 8 kernels */
1934  kernel=ParseKernelArray("3: 1,1,- 1,0,- 1,-,0");
1935  if (kernel == (KernelInfo *) NULL)
1936  return(kernel);
1937  kernel->type = type;
1938  ExpandRotateKernelInfo(kernel, 90.0);
1939  /* append the mirror versions too - no flip function yet */
1940  new_kernel=ParseKernelArray("3: 1,1,1 1,0,- -,-,0");
1941  if (new_kernel == (KernelInfo *) NULL)
1942  return(DestroyKernelInfo(kernel));
1943  new_kernel->type = type;
1944  ExpandRotateKernelInfo(new_kernel, 90.0);
1945  LastKernelInfo(kernel)->next = new_kernel;
1946  break;
1947  }
1948  case SkeletonKernel:
1949  {
1950  switch ( (int) args->rho ) {
1951  case 1:
1952  default:
1953  /* Traditional Skeleton...
1954  ** A cyclically rotated single kernel
1955  */
1956  kernel=AcquireKernelInfo("ThinSE:482",exception);
1957  if (kernel == (KernelInfo *) NULL)
1958  return(kernel);
1959  kernel->type = type;
1960  ExpandRotateKernelInfo(kernel, 45.0); /* 8 rotations */
1961  break;
1962  case 2:
1963  /* HIPR Variation of the cyclic skeleton
1964  ** Corners of the traditional method made more forgiving,
1965  ** but the retain the same cyclic order.
1966  */
1967  kernel=AcquireKernelInfo("ThinSE:482; ThinSE:87x90;",exception);
1968  if (kernel == (KernelInfo *) NULL)
1969  return(kernel);
1970  if (kernel->next == (KernelInfo *) NULL)
1971  return(DestroyKernelInfo(kernel));
1972  kernel->type = type;
1973  kernel->next->type = type;
1974  ExpandRotateKernelInfo(kernel, 90.0); /* 4 rotations of the 2 kernels */
1975  break;
1976  case 3:
1977  /* Dan Bloomberg Skeleton, from his paper on 3x3 thinning SE's
1978  ** "Connectivity-Preserving Morphological Image Thransformations"
1979  ** by Dan S. Bloomberg, available on Leptonica, Selected Papers,
1980  ** http://www.leptonica.com/papers/conn.pdf
1981  */
1982  kernel=AcquireKernelInfo("ThinSE:41; ThinSE:42; ThinSE:43",
1983  exception);
1984  if (kernel == (KernelInfo *) NULL)
1985  return(kernel);
1986  kernel->type = type;
1987  kernel->next->type = type;
1988  kernel->next->next->type = type;
1989  ExpandMirrorKernelInfo(kernel); /* 12 kernels total */
1990  break;
1991  }
1992  break;
1993  }
1994  case ThinSEKernel:
1995  { /* Special kernels for general thinning, while preserving connections
1996  ** "Connectivity-Preserving Morphological Image Thransformations"
1997  ** by Dan S. Bloomberg, available on Leptonica, Selected Papers,
1998  ** http://www.leptonica.com/papers/conn.pdf
1999  ** And
2000  ** http://tpgit.github.com/Leptonica/ccthin_8c_source.html
2001  **
2002  ** Note kernels do not specify the origin pixel, allowing them
2003  ** to be used for both thickening and thinning operations.
2004  */
2005  switch ( (int) args->rho ) {
2006  /* SE for 4-connected thinning */
2007  case 41: /* SE_4_1 */
2008  kernel=ParseKernelArray("3: -,-,1 0,-,1 -,-,1");
2009  break;
2010  case 42: /* SE_4_2 */
2011  kernel=ParseKernelArray("3: -,-,1 0,-,1 -,0,-");
2012  break;
2013  case 43: /* SE_4_3 */
2014  kernel=ParseKernelArray("3: -,0,- 0,-,1 -,-,1");
2015  break;
2016  case 44: /* SE_4_4 */
2017  kernel=ParseKernelArray("3: -,0,- 0,-,1 -,0,-");
2018  break;
2019  case 45: /* SE_4_5 */
2020  kernel=ParseKernelArray("3: -,0,1 0,-,1 -,0,-");
2021  break;
2022  case 46: /* SE_4_6 */
2023  kernel=ParseKernelArray("3: -,0,- 0,-,1 -,0,1");
2024  break;
2025  case 47: /* SE_4_7 */
2026  kernel=ParseKernelArray("3: -,1,1 0,-,1 -,0,-");
2027  break;
2028  case 48: /* SE_4_8 */
2029  kernel=ParseKernelArray("3: -,-,1 0,-,1 0,-,1");
2030  break;
2031  case 49: /* SE_4_9 */
2032  kernel=ParseKernelArray("3: 0,-,1 0,-,1 -,-,1");
2033  break;
2034  /* SE for 8-connected thinning - negatives of the above */
2035  case 81: /* SE_8_0 */
2036  kernel=ParseKernelArray("3: -,1,- 0,-,1 -,1,-");
2037  break;
2038  case 82: /* SE_8_2 */
2039  kernel=ParseKernelArray("3: -,1,- 0,-,1 0,-,-");
2040  break;
2041  case 83: /* SE_8_3 */
2042  kernel=ParseKernelArray("3: 0,-,- 0,-,1 -,1,-");
2043  break;
2044  case 84: /* SE_8_4 */
2045  kernel=ParseKernelArray("3: 0,-,- 0,-,1 0,-,-");
2046  break;
2047  case 85: /* SE_8_5 */
2048  kernel=ParseKernelArray("3: 0,-,1 0,-,1 0,-,-");
2049  break;
2050  case 86: /* SE_8_6 */
2051  kernel=ParseKernelArray("3: 0,-,- 0,-,1 0,-,1");
2052  break;
2053  case 87: /* SE_8_7 */
2054  kernel=ParseKernelArray("3: -,1,- 0,-,1 0,0,-");
2055  break;
2056  case 88: /* SE_8_8 */
2057  kernel=ParseKernelArray("3: -,1,- 0,-,1 0,1,-");
2058  break;
2059  case 89: /* SE_8_9 */
2060  kernel=ParseKernelArray("3: 0,1,- 0,-,1 -,1,-");
2061  break;
2062  /* Special combined SE kernels */
2063  case 423: /* SE_4_2 , SE_4_3 Combined Kernel */
2064  kernel=ParseKernelArray("3: -,-,1 0,-,- -,0,-");
2065  break;
2066  case 823: /* SE_8_2 , SE_8_3 Combined Kernel */
2067  kernel=ParseKernelArray("3: -,1,- -,-,1 0,-,-");
2068  break;
2069  case 481: /* SE_48_1 - General Connected Corner Kernel */
2070  kernel=ParseKernelArray("3: -,1,1 0,-,1 0,0,-");
2071  break;
2072  default:
2073  case 482: /* SE_48_2 - General Edge Kernel */
2074  kernel=ParseKernelArray("3: 0,-,1 0,-,1 0,-,1");
2075  break;
2076  }
2077  if (kernel == (KernelInfo *) NULL)
2078  return(kernel);
2079  kernel->type = type;
2080  RotateKernelInfo(kernel, args->sigma);
2081  break;
2082  }
2083  /*
2084  Distance Measuring Kernels
2085  */
2086  case ChebyshevKernel:
2087  {
2088  if (args->rho < 1.0)
2089  kernel->width = kernel->height = 3; /* default radius = 1 */
2090  else
2091  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2092  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2093 
2095  AcquireAlignedMemory(kernel->width,kernel->height*
2096  sizeof(*kernel->values)));
2097  if (kernel->values == (MagickRealType *) NULL)
2098  return(DestroyKernelInfo(kernel));
2099 
2100  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2101  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2102  kernel->positive_range += ( kernel->values[i] =
2103  args->sigma*MagickMax(fabs((double)u),fabs((double)v)) );
2104  kernel->maximum = kernel->values[0];
2105  break;
2106  }
2107  case ManhattanKernel:
2108  {
2109  if (args->rho < 1.0)
2110  kernel->width = kernel->height = 3; /* default radius = 1 */
2111  else
2112  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2113  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2114 
2116  AcquireAlignedMemory(kernel->width,kernel->height*
2117  sizeof(*kernel->values)));
2118  if (kernel->values == (MagickRealType *) NULL)
2119  return(DestroyKernelInfo(kernel));
2120 
2121  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2122  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2123  kernel->positive_range += ( kernel->values[i] =
2124  args->sigma*(labs((long) u)+labs((long) v)) );
2125  kernel->maximum = kernel->values[0];
2126  break;
2127  }
2128  case OctagonalKernel:
2129  {
2130  if (args->rho < 2.0)
2131  kernel->width = kernel->height = 5; /* default/minimum radius = 2 */
2132  else
2133  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2134  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2135 
2137  AcquireAlignedMemory(kernel->width,kernel->height*
2138  sizeof(*kernel->values)));
2139  if (kernel->values == (MagickRealType *) NULL)
2140  return(DestroyKernelInfo(kernel));
2141 
2142  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2143  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2144  {
2145  double
2146  r1 = MagickMax(fabs((double)u),fabs((double)v)),
2147  r2 = floor((double)(labs((long)u)+labs((long)v)+1)/1.5);
2148  kernel->positive_range += kernel->values[i] =
2149  args->sigma*MagickMax(r1,r2);
2150  }
2151  kernel->maximum = kernel->values[0];
2152  break;
2153  }
2154  case EuclideanKernel:
2155  {
2156  if (args->rho < 1.0)
2157  kernel->width = kernel->height = 3; /* default radius = 1 */
2158  else
2159  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2160  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2161 
2163  AcquireAlignedMemory(kernel->width,kernel->height*
2164  sizeof(*kernel->values)));
2165  if (kernel->values == (MagickRealType *) NULL)
2166  return(DestroyKernelInfo(kernel));
2167 
2168  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2169  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2170  kernel->positive_range += ( kernel->values[i] =
2171  args->sigma*sqrt((double)(u*u+v*v)) );
2172  kernel->maximum = kernel->values[0];
2173  break;
2174  }
2175  default:
2176  {
2177  /* No-Op Kernel - Basically just a single pixel on its own */
2178  kernel=ParseKernelArray("1:1");
2179  if (kernel == (KernelInfo *) NULL)
2180  return(kernel);
2181  kernel->type = UndefinedKernel;
2182  break;
2183  }
2184  break;
2185  }
2186  return(kernel);
2187 }
2188 
2189 /*
2190 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2191 % %
2192 % %
2193 % %
2194 % C l o n e K e r n e l I n f o %
2195 % %
2196 % %
2197 % %
2198 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2199 %
2200 % CloneKernelInfo() creates a new clone of the given Kernel List so that its
2201 % can be modified without effecting the original. The cloned kernel should
2202 % be destroyed using DestoryKernelInfo() when no longer needed.
2203 %
2204 % The format of the CloneKernelInfo method is:
2205 %
2206 % KernelInfo *CloneKernelInfo(const KernelInfo *kernel)
2207 %
2208 % A description of each parameter follows:
2209 %
2210 % o kernel: the Morphology/Convolution kernel to be cloned
2211 %
2212 */
2214 {
2215  ssize_t
2216  i;
2217 
2218  KernelInfo
2219  *new_kernel;
2220 
2221  assert(kernel != (KernelInfo *) NULL);
2222  new_kernel=(KernelInfo *) AcquireMagickMemory(sizeof(*kernel));
2223  if (new_kernel == (KernelInfo *) NULL)
2224  return(new_kernel);
2225  *new_kernel=(*kernel); /* copy values in structure */
2226 
2227  /* replace the values with a copy of the values */
2228  new_kernel->values=(MagickRealType *) MagickAssumeAligned(
2229  AcquireAlignedMemory(kernel->width,kernel->height*sizeof(*kernel->values)));
2230  if (new_kernel->values == (MagickRealType *) NULL)
2231  return(DestroyKernelInfo(new_kernel));
2232  for (i=0; i < (ssize_t) (kernel->width*kernel->height); i++)
2233  new_kernel->values[i]=kernel->values[i];
2234 
2235  /* Also clone the next kernel in the kernel list */
2236  if ( kernel->next != (KernelInfo *) NULL ) {
2237  new_kernel->next = CloneKernelInfo(kernel->next);
2238  if ( new_kernel->next == (KernelInfo *) NULL )
2239  return(DestroyKernelInfo(new_kernel));
2240  }
2241 
2242  return(new_kernel);
2243 }
2244 
2245 /*
2246 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2247 % %
2248 % %
2249 % %
2250 % D e s t r o y K e r n e l I n f o %
2251 % %
2252 % %
2253 % %
2254 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2255 %
2256 % DestroyKernelInfo() frees the memory used by a Convolution/Morphology
2257 % kernel.
2258 %
2259 % The format of the DestroyKernelInfo method is:
2260 %
2261 % KernelInfo *DestroyKernelInfo(KernelInfo *kernel)
2262 %
2263 % A description of each parameter follows:
2264 %
2265 % o kernel: the Morphology/Convolution kernel to be destroyed
2266 %
2267 */
2269 {
2270  assert(kernel != (KernelInfo *) NULL);
2271  if (kernel->next != (KernelInfo *) NULL)
2272  kernel->next=DestroyKernelInfo(kernel->next);
2273  kernel->values=(MagickRealType *) RelinquishAlignedMemory(kernel->values);
2274  kernel=(KernelInfo *) RelinquishMagickMemory(kernel);
2275  return(kernel);
2276 }
2277 
2278 /*
2279 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2280 % %
2281 % %
2282 % %
2283 + E x p a n d M i r r o r K e r n e l I n f o %
2284 % %
2285 % %
2286 % %
2287 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2288 %
2289 % ExpandMirrorKernelInfo() takes a single kernel, and expands it into a
2290 % sequence of 90-degree rotated kernels but providing a reflected 180
2291 % rotatation, before the -/+ 90-degree rotations.
2292 %
2293 % This special rotation order produces a better, more symetrical thinning of
2294 % objects.
2295 %
2296 % The format of the ExpandMirrorKernelInfo method is:
2297 %
2298 % void ExpandMirrorKernelInfo(KernelInfo *kernel)
2299 %
2300 % A description of each parameter follows:
2301 %
2302 % o kernel: the Morphology/Convolution kernel
2303 %
2304 % This function is only internel to this module, as it is not finalized,
2305 % especially with regard to non-orthogonal angles, and rotation of larger
2306 % 2D kernels.
2307 */
2308 
2309 #if 0
2310 static void FlopKernelInfo(KernelInfo *kernel)
2311  { /* Do a Flop by reversing each row. */
2312  size_t
2313  y;
2314  ssize_t
2315  x,r;
2316  double
2317  *k,t;
2318 
2319  for ( y=0, k=kernel->values; y < kernel->height; y++, k+=kernel->width)
2320  for ( x=0, r=kernel->width-1; x<kernel->width/2; x++, r--)
2321  t=k[x], k[x]=k[r], k[r]=t;
2322 
2323  kernel->x = kernel->width - kernel->x - 1;
2324  angle = fmod(angle+180.0, 360.0);
2325  }
2326 #endif
2327 
2329 {
2330  KernelInfo
2331  *clone,
2332  *last;
2333 
2334  last = kernel;
2335 
2336  clone = CloneKernelInfo(last);
2337  if (clone == (KernelInfo *) NULL)
2338  return;
2339  RotateKernelInfo(clone, 180); /* flip */
2340  LastKernelInfo(last)->next = clone;
2341  last = clone;
2342 
2343  clone = CloneKernelInfo(last);
2344  if (clone == (KernelInfo *) NULL)
2345  return;
2346  RotateKernelInfo(clone, 90); /* transpose */
2347  LastKernelInfo(last)->next = clone;
2348  last = clone;
2349 
2350  clone = CloneKernelInfo(last);
2351  if (clone == (KernelInfo *) NULL)
2352  return;
2353  RotateKernelInfo(clone, 180); /* flop */
2354  LastKernelInfo(last)->next = clone;
2355 
2356  return;
2357 }
2358 
2359 /*
2360 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2361 % %
2362 % %
2363 % %
2364 + E x p a n d R o t a t e K e r n e l I n f o %
2365 % %
2366 % %
2367 % %
2368 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2369 %
2370 % ExpandRotateKernelInfo() takes a kernel list, and expands it by rotating
2371 % incrementally by the angle given, until the kernel repeats.
2372 %
2373 % WARNING: 45 degree rotations only works for 3x3 kernels.
2374 % While 90 degree roatations only works for linear and square kernels
2375 %
2376 % The format of the ExpandRotateKernelInfo method is:
2377 %
2378 % void ExpandRotateKernelInfo(KernelInfo *kernel, double angle)
2379 %
2380 % A description of each parameter follows:
2381 %
2382 % o kernel: the Morphology/Convolution kernel
2383 %
2384 % o angle: angle to rotate in degrees
2385 %
2386 % This function is only internel to this module, as it is not finalized,
2387 % especially with regard to non-orthogonal angles, and rotation of larger
2388 % 2D kernels.
2389 */
2390 
2391 /* Internal Routine - Return true if two kernels are the same */
2393  const KernelInfo *kernel2)
2394 {
2395  size_t
2396  i;
2397 
2398  /* check size and origin location */
2399  if ( kernel1->width != kernel2->width
2400  || kernel1->height != kernel2->height
2401  || kernel1->x != kernel2->x
2402  || kernel1->y != kernel2->y )
2403  return MagickFalse;
2404 
2405  /* check actual kernel values */
2406  for (i=0; i < (kernel1->width*kernel1->height); i++) {
2407  /* Test for Nan equivalence */
2408  if ( IsNaN(kernel1->values[i]) && !IsNaN(kernel2->values[i]) )
2409  return MagickFalse;
2410  if ( IsNaN(kernel2->values[i]) && !IsNaN(kernel1->values[i]) )
2411  return MagickFalse;
2412  /* Test actual values are equivalent */
2413  if ( fabs(kernel1->values[i] - kernel2->values[i]) >= MagickEpsilon )
2414  return MagickFalse;
2415  }
2416 
2417  return MagickTrue;
2418 }
2419 
2420 static void ExpandRotateKernelInfo(KernelInfo *kernel,const double angle)
2421 {
2422  KernelInfo
2423  *clone_info,
2424  *last;
2425 
2426  clone_info=(KernelInfo *) NULL;
2427  last=kernel;
2428 DisableMSCWarning(4127)
2429  while (1) {
2431  clone_info=CloneKernelInfo(last);
2432  if (clone_info == (KernelInfo *) NULL)
2433  break;
2434  RotateKernelInfo(clone_info,angle);
2435  if (SameKernelInfo(kernel,clone_info) != MagickFalse)
2436  break;
2437  LastKernelInfo(last)->next=clone_info;
2438  last=clone_info;
2439  }
2440  if (clone_info != (KernelInfo *) NULL)
2441  clone_info=DestroyKernelInfo(clone_info); /* kernel repeated - junk */
2442  return;
2443 }
2444 
2445 /*
2446 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2447 % %
2448 % %
2449 % %
2450 + C a l c M e t a K e r n a l I n f o %
2451 % %
2452 % %
2453 % %
2454 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2455 %
2456 % CalcKernelMetaData() recalculate the KernelInfo meta-data of this kernel only,
2457 % using the kernel values. This should only ne used if it is not possible to
2458 % calculate that meta-data in some easier way.
2459 %
2460 % It is important that the meta-data is correct before ScaleKernelInfo() is
2461 % used to perform kernel normalization.
2462 %
2463 % The format of the CalcKernelMetaData method is:
2464 %
2465 % void CalcKernelMetaData(KernelInfo *kernel, const double scale )
2466 %
2467 % A description of each parameter follows:
2468 %
2469 % o kernel: the Morphology/Convolution kernel to modify
2470 %
2471 % WARNING: Minimum and Maximum values are assumed to include zero, even if
2472 % zero is not part of the kernel (as in Gaussian Derived kernels). This
2473 % however is not true for flat-shaped morphological kernels.
2474 %
2475 % WARNING: Only the specific kernel pointed to is modified, not a list of
2476 % multiple kernels.
2477 %
2478 % This is an internal function and not expected to be useful outside this
2479 % module. This could change however.
2480 */
2481 static void CalcKernelMetaData(KernelInfo *kernel)
2482 {
2483  size_t
2484  i;
2485 
2486  kernel->minimum = kernel->maximum = 0.0;
2487  kernel->negative_range = kernel->positive_range = 0.0;
2488  for (i=0; i < (kernel->width*kernel->height); i++)
2489  {
2490  if ( fabs(kernel->values[i]) < MagickEpsilon )
2491  kernel->values[i] = 0.0;
2492  ( kernel->values[i] < 0)
2493  ? ( kernel->negative_range += kernel->values[i] )
2494  : ( kernel->positive_range += kernel->values[i] );
2495  Minimize(kernel->minimum, kernel->values[i]);
2496  Maximize(kernel->maximum, kernel->values[i]);
2497  }
2498 
2499  return;
2500 }
2501 
2502 /*
2503 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2504 % %
2505 % %
2506 % %
2507 % M o r p h o l o g y A p p l y %
2508 % %
2509 % %
2510 % %
2511 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2512 %
2513 % MorphologyApply() applies a morphological method, multiple times using
2514 % a list of multiple kernels. This is the method that should be called by
2515 % other 'operators' that internally use morphology operations as part of
2516 % their processing.
2517 %
2518 % It is basically equivalent to as MorphologyImage() (see below) but without
2519 % any user controls. This allows internel programs to use this method to
2520 % perform a specific task without possible interference by any API user
2521 % supplied settings.
2522 %
2523 % It is MorphologyImage() task to extract any such user controls, and
2524 % pass them to this function for processing.
2525 %
2526 % More specifically all given kernels should already be scaled, normalised,
2527 % and blended appropriatally before being parred to this routine. The
2528 % appropriate bias, and compose (typically 'UndefinedComposeOp') given.
2529 %
2530 % The format of the MorphologyApply method is:
2531 %
2532 % Image *MorphologyApply(const Image *image,MorphologyMethod method,
2533 % const ssize_t iterations,const KernelInfo *kernel,
2534 % const CompositeMethod compose,const double bias,
2535 % ExceptionInfo *exception)
2536 %
2537 % A description of each parameter follows:
2538 %
2539 % o image: the source image
2540 %
2541 % o method: the morphology method to be applied.
2542 %
2543 % o iterations: apply the operation this many times (or no change).
2544 % A value of -1 means loop until no change found.
2545 % How this is applied may depend on the morphology method.
2546 % Typically this is a value of 1.
2547 %
2548 % o channel: the channel type.
2549 %
2550 % o kernel: An array of double representing the morphology kernel.
2551 %
2552 % o compose: How to handle or merge multi-kernel results.
2553 % If 'UndefinedCompositeOp' use default for the Morphology method.
2554 % If 'NoCompositeOp' force image to be re-iterated by each kernel.
2555 % Otherwise merge the results using the compose method given.
2556 %
2557 % o bias: Convolution Output Bias.
2558 %
2559 % o exception: return any errors or warnings in this structure.
2560 %
2561 */
2562 static ssize_t MorphologyPrimitive(const Image *image,Image *morphology_image,
2563  const MorphologyMethod method,const KernelInfo *kernel,const double bias,
2564  ExceptionInfo *exception)
2565 {
2566 #define MorphologyTag "Morphology/Image"
2567 
2568  CacheView
2569  *image_view,
2570  *morphology_view;
2571 
2572  OffsetInfo
2573  offset;
2574 
2575  ssize_t
2576  j,
2577  y;
2578 
2579  size_t
2580  *changes,
2581  changed,
2582  width;
2583 
2585  status;
2586 
2588  progress;
2589 
2590  assert(image != (Image *) NULL);
2591  assert(image->signature == MagickCoreSignature);
2592  assert(morphology_image != (Image *) NULL);
2593  assert(morphology_image->signature == MagickCoreSignature);
2594  assert(kernel != (KernelInfo *) NULL);
2595  assert(kernel->signature == MagickCoreSignature);
2596  assert(exception != (ExceptionInfo *) NULL);
2597  assert(exception->signature == MagickCoreSignature);
2598  status=MagickTrue;
2599  progress=0;
2600  image_view=AcquireVirtualCacheView(image,exception);
2601  morphology_view=AcquireAuthenticCacheView(morphology_image,exception);
2602  width=image->columns+kernel->width-1;
2603  offset.x=0;
2604  offset.y=0;
2605  switch (method)
2606  {
2607  case ConvolveMorphology:
2608  case DilateMorphology:
2611  {
2612  /*
2613  Kernel needs to used with reflection about origin.
2614  */
2615  offset.x=(ssize_t) kernel->width-kernel->x-1;
2616  offset.y=(ssize_t) kernel->height-kernel->y-1;
2617  break;
2618  }
2619  case ErodeMorphology:
2621  case HitAndMissMorphology:
2622  case ThinningMorphology:
2623  case ThickenMorphology:
2624  {
2625  offset.x=kernel->x;
2626  offset.y=kernel->y;
2627  break;
2628  }
2629  default:
2630  {
2632  "InvalidOption","`%s'","Not a Primitive Morphology Method");
2633  break;
2634  }
2635  }
2636  changed=0;
2637  changes=(size_t *) AcquireQuantumMemory(GetOpenMPMaximumThreads(),
2638  sizeof(*changes));
2639  if (changes == (size_t *) NULL)
2640  ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
2641  for (j=0; j < (ssize_t) GetOpenMPMaximumThreads(); j++)
2642  changes[j]=0;
2643 
2644  if ((method == ConvolveMorphology) && (kernel->width == 1))
2645  {
2646  ssize_t
2647  x;
2648 
2649  /*
2650  Special handling (for speed) of vertical (blur) kernels. This performs
2651  its handling in columns rather than in rows. This is only done
2652  for convolve as it is the only method that generates very large 1-D
2653  vertical kernels (such as a 'BlurKernel')
2654  */
2655 #if defined(MAGICKCORE_OPENMP_SUPPORT)
2656  #pragma omp parallel for schedule(static) shared(progress,status) \
2657  magick_number_threads(image,morphology_image,image->columns,1)
2658 #endif
2659  for (x=0; x < (ssize_t) image->columns; x++)
2660  {
2661  const int
2662  id = GetOpenMPThreadId();
2663 
2664  const Quantum
2665  *magick_restrict p;
2666 
2667  Quantum
2668  *magick_restrict q;
2669 
2670  ssize_t
2671  r;
2672 
2673  ssize_t
2674  center;
2675 
2676  if (status == MagickFalse)
2677  continue;
2678  p=GetCacheViewVirtualPixels(image_view,x,-offset.y,1,image->rows+
2679  kernel->height-1,exception);
2680  q=GetCacheViewAuthenticPixels(morphology_view,x,0,1,
2681  morphology_image->rows,exception);
2682  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
2683  {
2684  status=MagickFalse;
2685  continue;
2686  }
2687  center=(ssize_t) GetPixelChannels(image)*offset.y;
2688  for (r=0; r < (ssize_t) image->rows; r++)
2689  {
2690  ssize_t
2691  i;
2692 
2693  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
2694  {
2695  double
2696  alpha,
2697  gamma,
2698  pixel;
2699 
2700  PixelChannel
2701  channel;
2702 
2703  PixelTrait
2704  morphology_traits,
2705  traits;
2706 
2707  const MagickRealType
2708  *magick_restrict k;
2709 
2710  const Quantum
2711  *magick_restrict pixels;
2712 
2713  ssize_t
2714  v;
2715 
2716  size_t
2717  count;
2718 
2719  channel=GetPixelChannelChannel(image,i);
2720  traits=GetPixelChannelTraits(image,channel);
2721  morphology_traits=GetPixelChannelTraits(morphology_image,channel);
2722  if ((traits == UndefinedPixelTrait) ||
2723  (morphology_traits == UndefinedPixelTrait))
2724  continue;
2725  if ((traits & CopyPixelTrait) != 0)
2726  {
2727  SetPixelChannel(morphology_image,channel,p[center+i],q);
2728  continue;
2729  }
2730  k=(&kernel->values[kernel->height-1]);
2731  pixels=p;
2732  pixel=bias;
2733  gamma=1.0;
2734  count=0;
2735  if (((image->alpha_trait & BlendPixelTrait) == 0) ||
2736  ((morphology_traits & BlendPixelTrait) == 0))
2737  for (v=0; v < (ssize_t) kernel->height; v++)
2738  {
2739  if (!IsNaN(*k))
2740  {
2741  pixel+=(*k)*pixels[i];
2742  count++;
2743  }
2744  k--;
2745  pixels+=GetPixelChannels(image);
2746  }
2747  else
2748  {
2749  gamma=0.0;
2750  for (v=0; v < (ssize_t) kernel->height; v++)
2751  {
2752  if (!IsNaN(*k))
2753  {
2754  alpha=(double) (QuantumScale*GetPixelAlpha(image,pixels));
2755  pixel+=alpha*(*k)*pixels[i];
2756  gamma+=alpha*(*k);
2757  count++;
2758  }
2759  k--;
2760  pixels+=GetPixelChannels(image);
2761  }
2762  }
2763  if (fabs(pixel-p[center+i]) > MagickEpsilon)
2764  changes[id]++;
2765  gamma=PerceptibleReciprocal(gamma);
2766  if (count != 0)
2767  gamma*=(double) kernel->height/count;
2768  SetPixelChannel(morphology_image,channel,ClampToQuantum(gamma*
2769  pixel),q);
2770  }
2771  p+=GetPixelChannels(image);
2772  q+=GetPixelChannels(morphology_image);
2773  }
2774  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
2775  status=MagickFalse;
2776  if (image->progress_monitor != (MagickProgressMonitor) NULL)
2777  {
2779  proceed;
2780 
2781 #if defined(MAGICKCORE_OPENMP_SUPPORT)
2782  #pragma omp atomic
2783 #endif
2784  progress++;
2785  proceed=SetImageProgress(image,MorphologyTag,progress,image->rows);
2786  if (proceed == MagickFalse)
2787  status=MagickFalse;
2788  }
2789  }
2790  morphology_image->type=image->type;
2791  morphology_view=DestroyCacheView(morphology_view);
2792  image_view=DestroyCacheView(image_view);
2793  for (j=0; j < (ssize_t) GetOpenMPMaximumThreads(); j++)
2794  changed+=changes[j];
2795  changes=(size_t *) RelinquishMagickMemory(changes);
2796  return(status ? (ssize_t) changed : 0);
2797  }
2798  /*
2799  Normal handling of horizontal or rectangular kernels (row by row).
2800  */
2801 #if defined(MAGICKCORE_OPENMP_SUPPORT)
2802  #pragma omp parallel for schedule(static) shared(progress,status) \
2803  magick_number_threads(image,morphology_image,image->rows,1)
2804 #endif
2805  for (y=0; y < (ssize_t) image->rows; y++)
2806  {
2807  const int
2808  id = GetOpenMPThreadId();
2809 
2810  const Quantum
2811  *magick_restrict p;
2812 
2813  Quantum
2814  *magick_restrict q;
2815 
2816  ssize_t
2817  x;
2818 
2819  ssize_t
2820  center;
2821 
2822  if (status == MagickFalse)
2823  continue;
2824  p=GetCacheViewVirtualPixels(image_view,-offset.x,y-offset.y,width,
2825  kernel->height,exception);
2826  q=GetCacheViewAuthenticPixels(morphology_view,0,y,morphology_image->columns,
2827  1,exception);
2828  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
2829  {
2830  status=MagickFalse;
2831  continue;
2832  }
2833  center=(ssize_t) (GetPixelChannels(image)*width*offset.y+
2834  GetPixelChannels(image)*offset.x);
2835  for (x=0; x < (ssize_t) image->columns; x++)
2836  {
2837  ssize_t
2838  i;
2839 
2840  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
2841  {
2842  double
2843  alpha,
2844  gamma,
2845  intensity,
2846  maximum,
2847  minimum,
2848  pixel;
2849 
2850  PixelChannel
2851  channel;
2852 
2853  PixelTrait
2854  morphology_traits,
2855  traits;
2856 
2857  const MagickRealType
2858  *magick_restrict k;
2859 
2860  const Quantum
2861  *magick_restrict pixels,
2862  *magick_restrict quantum_pixels;
2863 
2864  ssize_t
2865  u;
2866 
2867  size_t
2868  count;
2869 
2870  ssize_t
2871  v;
2872 
2873  channel=GetPixelChannelChannel(image,i);
2874  traits=GetPixelChannelTraits(image,channel);
2875  morphology_traits=GetPixelChannelTraits(morphology_image,channel);
2876  if ((traits == UndefinedPixelTrait) ||
2877  (morphology_traits == UndefinedPixelTrait))
2878  continue;
2879  if ((traits & CopyPixelTrait) != 0)
2880  {
2881  SetPixelChannel(morphology_image,channel,p[center+i],q);
2882  continue;
2883  }
2884  pixels=p;
2885  quantum_pixels=(const Quantum *) NULL;
2886  maximum=0.0;
2887  minimum=(double) QuantumRange;
2888  switch (method)
2889  {
2890  case ConvolveMorphology:
2891  {
2892  pixel=bias;
2893  break;
2894  }
2895  case DilateMorphology:
2897  {
2898  pixel=0.0;
2899  break;
2900  }
2901  case HitAndMissMorphology:
2902  case ErodeMorphology:
2903  {
2904  pixel=QuantumRange;
2905  break;
2906  }
2907  default:
2908  {
2909  pixel=(double) p[center+i];
2910  break;
2911  }
2912  }
2913  count=0;
2914  gamma=1.0;
2915  switch (method)
2916  {
2917  case ConvolveMorphology:
2918  {
2919  /*
2920  Weighted Average of pixels using reflected kernel
2921 
2922  For correct working of this operation for asymetrical kernels,
2923  the kernel needs to be applied in its reflected form. That is
2924  its values needs to be reversed.
2925 
2926  Correlation is actually the same as this but without reflecting
2927  the kernel, and thus 'lower-level' that Convolution. However as
2928  Convolution is the more common method used, and it does not
2929  really cost us much in terms of processing to use a reflected
2930  kernel, so it is Convolution that is implemented.
2931 
2932  Correlation will have its kernel reflected before calling this
2933  function to do a Convolve.
2934 
2935  For more details of Correlation vs Convolution see
2936  http://www.cs.umd.edu/~djacobs/CMSC426/Convolution.pdf
2937  */
2938  k=(&kernel->values[kernel->width*kernel->height-1]);
2939  if (((image->alpha_trait & BlendPixelTrait) == 0) ||
2940  ((morphology_traits & BlendPixelTrait) == 0))
2941  {
2942  /*
2943  No alpha blending.
2944  */
2945  for (v=0; v < (ssize_t) kernel->height; v++)
2946  {
2947  for (u=0; u < (ssize_t) kernel->width; u++)
2948  {
2949  if (!IsNaN(*k))
2950  {
2951  pixel+=(*k)*pixels[i];
2952  count++;
2953  }
2954  k--;
2955  pixels+=GetPixelChannels(image);
2956  }
2957  pixels+=(image->columns-1)*GetPixelChannels(image);
2958  }
2959  break;
2960  }
2961  /*
2962  Alpha blending.
2963  */
2964  gamma=0.0;
2965  for (v=0; v < (ssize_t) kernel->height; v++)
2966  {
2967  for (u=0; u < (ssize_t) kernel->width; u++)
2968  {
2969  if (!IsNaN(*k))
2970  {
2971  alpha=(double) (QuantumScale*GetPixelAlpha(image,pixels));
2972  pixel+=alpha*(*k)*pixels[i];
2973  gamma+=alpha*(*k);
2974  count++;
2975  }
2976  k--;
2977  pixels+=GetPixelChannels(image);
2978  }
2979  pixels+=(image->columns-1)*GetPixelChannels(image);
2980  }
2981  break;
2982  }
2983  case ErodeMorphology:
2984  {
2985  /*
2986  Minimum value within kernel neighbourhood.
2987 
2988  The kernel is not reflected for this operation. In normal
2989  Greyscale Morphology, the kernel value should be added
2990  to the real value, this is currently not done, due to the
2991  nature of the boolean kernels being used.
2992  */
2993  k=kernel->values;
2994  for (v=0; v < (ssize_t) kernel->height; v++)
2995  {
2996  for (u=0; u < (ssize_t) kernel->width; u++)
2997  {
2998  if (!IsNaN(*k) && (*k >= 0.5))
2999  {
3000  if ((double) pixels[i] < pixel)
3001  pixel=(double) pixels[i];
3002  }
3003  k++;
3004  pixels+=GetPixelChannels(image);
3005  }
3006  pixels+=(image->columns-1)*GetPixelChannels(image);
3007  }
3008  break;
3009  }
3010  case DilateMorphology:
3011  {
3012  /*
3013  Maximum value within kernel neighbourhood.
3014 
3015  For correct working of this operation for asymetrical kernels,
3016  the kernel needs to be applied in its reflected form. That is
3017  its values needs to be reversed.
3018 
3019  In normal Greyscale Morphology, the kernel value should be
3020  added to the real value, this is currently not done, due to the
3021  nature of the boolean kernels being used.
3022  */
3023  k=(&kernel->values[kernel->width*kernel->height-1]);
3024  for (v=0; v < (ssize_t) kernel->height; v++)
3025  {
3026  for (u=0; u < (ssize_t) kernel->width; u++)
3027  {
3028  if (!IsNaN(*k) && (*k > 0.5))
3029  {
3030  if ((double) pixels[i] > pixel)
3031  pixel=(double) pixels[i];
3032  }
3033  k--;
3034  pixels+=GetPixelChannels(image);
3035  }
3036  pixels+=(image->columns-1)*GetPixelChannels(image);
3037  }
3038  break;
3039  }
3040  case HitAndMissMorphology:
3041  case ThinningMorphology:
3042  case ThickenMorphology:
3043  {
3044  /*
3045  Minimum of foreground pixel minus maxumum of background pixels.
3046 
3047  The kernel is not reflected for this operation, and consists
3048  of both foreground and background pixel neighbourhoods, 0.0 for
3049  background, and 1.0 for foreground with either Nan or 0.5 values
3050  for don't care.
3051 
3052  This never produces a meaningless negative result. Such results
3053  cause Thinning/Thicken to not work correctly when used against a
3054  greyscale image.
3055  */
3056  k=kernel->values;
3057  for (v=0; v < (ssize_t) kernel->height; v++)
3058  {
3059  for (u=0; u < (ssize_t) kernel->width; u++)
3060  {
3061  if (!IsNaN(*k))
3062  {
3063  if (*k > 0.7)
3064  {
3065  if ((double) pixels[i] < pixel)
3066  pixel=(double) pixels[i];
3067  }
3068  else
3069  if (*k < 0.3)
3070  {
3071  if ((double) pixels[i] > maximum)
3072  maximum=(double) pixels[i];
3073  }
3074  count++;
3075  }
3076  k++;
3077  pixels+=GetPixelChannels(image);
3078  }
3079  pixels+=(image->columns-1)*GetPixelChannels(image);
3080  }
3081  pixel-=maximum;
3082  if (pixel < 0.0)
3083  pixel=0.0;
3084  if (method == ThinningMorphology)
3085  pixel=(double) p[center+i]-pixel;
3086  else
3087  if (method == ThickenMorphology)
3088  pixel+=(double) p[center+i]+pixel;
3089  break;
3090  }
3092  {
3093  /*
3094  Select pixel with minimum intensity within kernel neighbourhood.
3095 
3096  The kernel is not reflected for this operation.
3097  */
3098  k=kernel->values;
3099  for (v=0; v < (ssize_t) kernel->height; v++)
3100  {
3101  for (u=0; u < (ssize_t) kernel->width; u++)
3102  {
3103  if (!IsNaN(*k) && (*k >= 0.5))
3104  {
3105  intensity=(double) GetPixelIntensity(image,pixels);
3106  if (intensity < minimum)
3107  {
3108  quantum_pixels=pixels;
3109  pixel=(double) pixels[i];
3110  minimum=intensity;
3111  }
3112  count++;
3113  }
3114  k++;
3115  pixels+=GetPixelChannels(image);
3116  }
3117  pixels+=(image->columns-1)*GetPixelChannels(image);
3118  }
3119  break;
3120  }
3122  {
3123  /*
3124  Select pixel with maximum intensity within kernel neighbourhood.
3125 
3126  The kernel is not reflected for this operation.
3127  */
3128  k=(&kernel->values[kernel->width*kernel->height-1]);
3129  for (v=0; v < (ssize_t) kernel->height; v++)
3130  {
3131  for (u=0; u < (ssize_t) kernel->width; u++)
3132  {
3133  if (!IsNaN(*k) && (*k >= 0.5))
3134  {
3135  intensity=(double) GetPixelIntensity(image,pixels);
3136  if (intensity > maximum)
3137  {
3138  pixel=(double) pixels[i];
3139  quantum_pixels=pixels;
3140  maximum=intensity;
3141  }
3142  count++;
3143  }
3144  k--;
3145  pixels+=GetPixelChannels(image);
3146  }
3147  pixels+=(image->columns-1)*GetPixelChannels(image);
3148  }
3149  break;
3150  }
3152  {
3153  /*
3154  Compute th iterative distance from black edge of a white image
3155  shape. Essentially white values are decreased to the smallest
3156  'distance from edge' it can find.
3157 
3158  It works by adding kernel values to the neighbourhood, and
3159  select the minimum value found. The kernel is rotated before
3160  use, so kernel distances match resulting distances, when a user
3161  provided asymmetric kernel is applied.
3162 
3163  This code is nearly identical to True GrayScale Morphology but
3164  not quite.
3165 
3166  GreyDilate Kernel values added, maximum value found Kernel is
3167  rotated before use.
3168 
3169  GrayErode: Kernel values subtracted and minimum value found No
3170  kernel rotation used.
3171 
3172  Note the Iterative Distance method is essentially a
3173  GrayErode, but with negative kernel values, and kernel rotation
3174  applied.
3175  */
3176  k=(&kernel->values[kernel->width*kernel->height-1]);
3177  for (v=0; v < (ssize_t) kernel->height; v++)
3178  {
3179  for (u=0; u < (ssize_t) kernel->width; u++)
3180  {
3181  if (!IsNaN(*k))
3182  {
3183  if ((pixels[i]+(*k)) < pixel)
3184  pixel=(double) pixels[i]+(*k);
3185  count++;
3186  }
3187  k--;
3188  pixels+=GetPixelChannels(image);
3189  }
3190  pixels+=(image->columns-1)*GetPixelChannels(image);
3191  }
3192  break;
3193  }
3194  case UndefinedMorphology:
3195  default:
3196  break;
3197  }
3198  if (fabs(pixel-p[center+i]) > MagickEpsilon)
3199  changes[id]++;
3200  if (quantum_pixels != (const Quantum *) NULL)
3201  {
3202  SetPixelChannel(morphology_image,channel,quantum_pixels[i],q);
3203  continue;
3204  }
3205  gamma=PerceptibleReciprocal(gamma);
3206  if (count != 0)
3207  gamma*=(double) kernel->height*kernel->width/count;
3208  SetPixelChannel(morphology_image,channel,ClampToQuantum(gamma*pixel),q);
3209  }
3210  p+=GetPixelChannels(image);
3211  q+=GetPixelChannels(morphology_image);
3212  }
3213  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
3214  status=MagickFalse;
3215  if (image->progress_monitor != (MagickProgressMonitor) NULL)
3216  {
3218  proceed;
3219 
3220 #if defined(MAGICKCORE_OPENMP_SUPPORT)
3221  #pragma omp atomic
3222 #endif
3223  progress++;
3224  proceed=SetImageProgress(image,MorphologyTag,progress,image->rows);
3225  if (proceed == MagickFalse)
3226  status=MagickFalse;
3227  }
3228  }
3229  morphology_view=DestroyCacheView(morphology_view);
3230  image_view=DestroyCacheView(image_view);
3231  for (j=0; j < (ssize_t) GetOpenMPMaximumThreads(); j++)
3232  changed+=changes[j];
3233  changes=(size_t *) RelinquishMagickMemory(changes);
3234  return(status ? (ssize_t) changed : -1);
3235 }
3236 
3237 /*
3238  This is almost identical to the MorphologyPrimative() function above, but
3239  applies the primitive directly to the actual image using two passes, once in
3240  each direction, with the results of the previous (and current) row being
3241  re-used.
3242 
3243  That is after each row is 'Sync'ed' into the image, the next row makes use of
3244  those values as part of the calculation of the next row. It repeats, but
3245  going in the oppisite (bottom-up) direction.
3246 
3247  Because of this 're-use of results' this function can not make use of multi-
3248  threaded, parellel processing.
3249 */
3250 static ssize_t MorphologyPrimitiveDirect(Image *image,
3251  const MorphologyMethod method,const KernelInfo *kernel,
3252  ExceptionInfo *exception)
3253 {
3254  CacheView
3255  *morphology_view,
3256  *image_view;
3257 
3259  status;
3260 
3262  progress;
3263 
3264  OffsetInfo
3265  offset;
3266 
3267  size_t
3268  width,
3269  changed;
3270 
3271  ssize_t
3272  y;
3273 
3274  assert(image != (Image *) NULL);
3275  assert(image->signature == MagickCoreSignature);
3276  assert(kernel != (KernelInfo *) NULL);
3277  assert(kernel->signature == MagickCoreSignature);
3278  assert(exception != (ExceptionInfo *) NULL);
3279  assert(exception->signature == MagickCoreSignature);
3280  status=MagickTrue;
3281  changed=0;
3282  progress=0;
3283  switch(method)
3284  {
3285  case DistanceMorphology:
3286  case VoronoiMorphology:
3287  {
3288  /*
3289  Kernel reflected about origin.
3290  */
3291  offset.x=(ssize_t) kernel->width-kernel->x-1;
3292  offset.y=(ssize_t) kernel->height-kernel->y-1;
3293  break;
3294  }
3295  default:
3296  {
3297  offset.x=kernel->x;
3298  offset.y=kernel->y;
3299  break;
3300  }
3301  }
3302  /*
3303  Two views into same image, do not thread.
3304  */
3305  image_view=AcquireVirtualCacheView(image,exception);
3306  morphology_view=AcquireAuthenticCacheView(image,exception);
3307  width=image->columns+kernel->width-1;
3308  for (y=0; y < (ssize_t) image->rows; y++)
3309  {
3310  const Quantum
3311  *magick_restrict p;
3312 
3313  Quantum
3314  *magick_restrict q;
3315 
3316  ssize_t
3317  x;
3318 
3319  /*
3320  Read virtual pixels, and authentic pixels, from the same image! We read
3321  using virtual to get virtual pixel handling, but write back into the same
3322  image.
3323 
3324  Only top half of kernel is processed as we do a single pass downward
3325  through the image iterating the distance function as we go.
3326  */
3327  if (status == MagickFalse)
3328  continue;
3329  p=GetCacheViewVirtualPixels(image_view,-offset.x,y-offset.y,width,(size_t)
3330  offset.y+1,exception);
3331  q=GetCacheViewAuthenticPixels(morphology_view,0,y,image->columns,1,
3332  exception);
3333  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
3334  {
3335  status=MagickFalse;
3336  continue;
3337  }
3338  for (x=0; x < (ssize_t) image->columns; x++)
3339  {
3340  ssize_t
3341  i;
3342 
3343  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
3344  {
3345  double
3346  pixel;
3347 
3348  PixelChannel
3349  channel;
3350 
3351  PixelTrait
3352  traits;
3353 
3354  const MagickRealType
3355  *magick_restrict k;
3356 
3357  const Quantum
3358  *magick_restrict pixels;
3359 
3360  ssize_t
3361  u;
3362 
3363  ssize_t
3364  v;
3365 
3366  channel=GetPixelChannelChannel(image,i);
3367  traits=GetPixelChannelTraits(image,channel);
3368  if (traits == UndefinedPixelTrait)
3369  continue;
3370  if ((traits & CopyPixelTrait) != 0)
3371  continue;
3372  pixels=p;
3373  pixel=(double) QuantumRange;
3374  switch (method)
3375  {
3376  case DistanceMorphology:
3377  {
3378  k=(&kernel->values[kernel->width*kernel->height-1]);
3379  for (v=0; v <= offset.y; v++)
3380  {
3381  for (u=0; u < (ssize_t) kernel->width; u++)
3382  {
3383  if (!IsNaN(*k))
3384  {
3385  if ((pixels[i]+(*k)) < pixel)
3386  pixel=(double) pixels[i]+(*k);
3387  }
3388  k--;
3389  pixels+=GetPixelChannels(image);
3390  }
3391  pixels+=(image->columns-1)*GetPixelChannels(image);
3392  }
3393  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3394  pixels=q-offset.x*GetPixelChannels(image);
3395  for (u=0; u < offset.x; u++)
3396  {
3397  if (!IsNaN(*k) && ((x+u-offset.x) >= 0))
3398  {
3399  if ((pixels[i]+(*k)) < pixel)
3400  pixel=(double) pixels[i]+(*k);
3401  }
3402  k--;
3403  pixels+=GetPixelChannels(image);
3404  }
3405  break;
3406  }
3407  case VoronoiMorphology:
3408  {
3409  k=(&kernel->values[kernel->width*kernel->height-1]);
3410  for (v=0; v < offset.y; v++)
3411  {
3412  for (u=0; u < (ssize_t) kernel->width; u++)
3413  {
3414  if (!IsNaN(*k))
3415  {
3416  if ((pixels[i]+(*k)) < pixel)
3417  pixel=(double) pixels[i]+(*k);
3418  }
3419  k--;
3420  pixels+=GetPixelChannels(image);
3421  }
3422  pixels+=(image->columns-1)*GetPixelChannels(image);
3423  }
3424  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3425  pixels=q-offset.x*GetPixelChannels(image);
3426  for (u=0; u < offset.x; u++)
3427  {
3428  if (!IsNaN(*k) && ((x+u-offset.x) >= 0))
3429  {
3430  if ((pixels[i]+(*k)) < pixel)
3431  pixel=(double) pixels[i]+(*k);
3432  }
3433  k--;
3434  pixels+=GetPixelChannels(image);
3435  }
3436  break;
3437  }
3438  default:
3439  break;
3440  }
3441  if (fabs(pixel-q[i]) > MagickEpsilon)
3442  changed++;
3443  q[i]=ClampToQuantum(pixel);
3444  }
3445  p+=GetPixelChannels(image);
3446  q+=GetPixelChannels(image);
3447  }
3448  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
3449  status=MagickFalse;
3450  if (image->progress_monitor != (MagickProgressMonitor) NULL)
3451  {
3453  proceed;
3454 
3455 #if defined(MAGICKCORE_OPENMP_SUPPORT)
3456  #pragma omp atomic
3457 #endif
3458  progress++;
3459  proceed=SetImageProgress(image,MorphologyTag,progress,2*image->rows);
3460  if (proceed == MagickFalse)
3461  status=MagickFalse;
3462  }
3463  }
3464  morphology_view=DestroyCacheView(morphology_view);
3465  image_view=DestroyCacheView(image_view);
3466  /*
3467  Do the reverse pass through the image.
3468  */
3469  image_view=AcquireVirtualCacheView(image,exception);
3470  morphology_view=AcquireAuthenticCacheView(image,exception);
3471  for (y=(ssize_t) image->rows-1; y >= 0; y--)
3472  {
3473  const Quantum
3474  *magick_restrict p;
3475 
3476  Quantum
3477  *magick_restrict q;
3478 
3479  ssize_t
3480  x;
3481 
3482  /*
3483  Read virtual pixels, and authentic pixels, from the same image. We
3484  read using virtual to get virtual pixel handling, but write back
3485  into the same image.
3486 
3487  Only the bottom half of the kernel is processed as we up the image.
3488  */
3489  if (status == MagickFalse)
3490  continue;
3491  p=GetCacheViewVirtualPixels(image_view,-offset.x,y,width,(size_t)
3492  kernel->y+1,exception);
3493  q=GetCacheViewAuthenticPixels(morphology_view,0,y,image->columns,1,
3494  exception);
3495  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
3496  {
3497  status=MagickFalse;
3498  continue;
3499  }
3500  p+=(image->columns-1)*GetPixelChannels(image);
3501  q+=(image->columns-1)*GetPixelChannels(image);
3502  for (x=(ssize_t) image->columns-1; x >= 0; x--)
3503  {
3504  ssize_t
3505  i;
3506 
3507  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
3508  {
3509  double
3510  pixel;
3511 
3512  PixelChannel
3513  channel;
3514 
3515  PixelTrait
3516  traits;
3517 
3518  const MagickRealType
3519  *magick_restrict k;
3520 
3521  const Quantum
3522  *magick_restrict pixels;
3523 
3524  ssize_t
3525  u;
3526 
3527  ssize_t
3528  v;
3529 
3530  channel=GetPixelChannelChannel(image,i);
3531  traits=GetPixelChannelTraits(image,channel);
3532  if (traits == UndefinedPixelTrait)
3533  continue;
3534  if ((traits & CopyPixelTrait) != 0)
3535  continue;
3536  pixels=p;
3537  pixel=(double) QuantumRange;
3538  switch (method)
3539  {
3540  case DistanceMorphology:
3541  {
3542  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3543  for (v=offset.y; v < (ssize_t) kernel->height; v++)
3544  {
3545  for (u=0; u < (ssize_t) kernel->width; u++)
3546  {
3547  if (!IsNaN(*k))
3548  {
3549  if ((pixels[i]+(*k)) < pixel)
3550  pixel=(double) pixels[i]+(*k);
3551  }
3552  k--;
3553  pixels+=GetPixelChannels(image);
3554  }
3555  pixels+=(image->columns-1)*GetPixelChannels(image);
3556  }
3557  k=(&kernel->values[kernel->width*kernel->y+kernel->x-1]);
3558  pixels=q;
3559  for (u=offset.x+1; u < (ssize_t) kernel->width; u++)
3560  {
3561  pixels+=GetPixelChannels(image);
3562  if (!IsNaN(*k) && ((x+u-offset.x) < (ssize_t) image->columns))
3563  {
3564  if ((pixels[i]+(*k)) < pixel)
3565  pixel=(double) pixels[i]+(*k);
3566  }
3567  k--;
3568  }
3569  break;
3570  }
3571  case VoronoiMorphology:
3572  {
3573  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3574  for (v=offset.y; v < (ssize_t) kernel->height; v++)
3575  {
3576  for (u=0; u < (ssize_t) kernel->width; u++)
3577  {
3578  if (!IsNaN(*k))
3579  {
3580  if ((pixels[i]+(*k)) < pixel)
3581  pixel=(double) pixels[i]+(*k);
3582  }
3583  k--;
3584  pixels+=GetPixelChannels(image);
3585  }
3586  pixels+=(image->columns-1)*GetPixelChannels(image);
3587  }
3588  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3589  pixels=q;
3590  for (u=offset.x+1; u < (ssize_t) kernel->width; u++)
3591  {
3592  pixels+=GetPixelChannels(image);
3593  if (!IsNaN(*k) && ((x+u-offset.x) < (ssize_t) image->columns))
3594  {
3595  if ((pixels[i]+(*k)) < pixel)
3596  pixel=(double) pixels[i]+(*k);
3597  }
3598  k--;
3599  }
3600  break;
3601  }
3602  default:
3603  break;
3604  }
3605  if (fabs(pixel-q[i]) > MagickEpsilon)
3606  changed++;
3607  q[i]=ClampToQuantum(pixel);
3608  }
3609  p-=GetPixelChannels(image);
3610  q-=GetPixelChannels(image);
3611  }
3612  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
3613  status=MagickFalse;
3614  if (image->progress_monitor != (MagickProgressMonitor) NULL)
3615  {
3617  proceed;
3618 
3619 #if defined(MAGICKCORE_OPENMP_SUPPORT)
3620  #pragma omp atomic
3621 #endif
3622  progress++;
3623  proceed=SetImageProgress(image,MorphologyTag,progress,2*image->rows);
3624  if (proceed == MagickFalse)
3625  status=MagickFalse;
3626  }
3627  }
3628  morphology_view=DestroyCacheView(morphology_view);
3629  image_view=DestroyCacheView(image_view);
3630  return(status ? (ssize_t) changed : -1);
3631 }
3632 
3633 /*
3634  Apply a Morphology by calling one of the above low level primitive
3635  application functions. This function handles any iteration loops,
3636  composition or re-iteration of results, and compound morphology methods that
3637  is based on multiple low-level (staged) morphology methods.
3638 
3639  Basically this provides the complex glue between the requested morphology
3640  method and raw low-level implementation (above).
3641 */
3643  const MorphologyMethod method, const ssize_t iterations,
3644  const KernelInfo *kernel, const CompositeOperator compose,const double bias,
3645  ExceptionInfo *exception)
3646 {
3648  curr_compose;
3649 
3650  Image
3651  *curr_image, /* Image we are working with or iterating */
3652  *work_image, /* secondary image for primitive iteration */
3653  *save_image, /* saved image - for 'edge' method only */
3654  *rslt_image; /* resultant image - after multi-kernel handling */
3655 
3656  KernelInfo
3657  *reflected_kernel, /* A reflected copy of the kernel (if needed) */
3658  *norm_kernel, /* the current normal un-reflected kernel */
3659  *rflt_kernel, /* the current reflected kernel (if needed) */
3660  *this_kernel; /* the kernel being applied */
3661 
3663  primitive; /* the current morphology primitive being applied */
3664 
3666  rslt_compose; /* multi-kernel compose method for results to use */
3667 
3669  special, /* do we use a direct modify function? */
3670  verbose; /* verbose output of results */
3671 
3672  size_t
3673  method_loop, /* Loop 1: number of compound method iterations (norm 1) */
3674  method_limit, /* maximum number of compound method iterations */
3675  kernel_number, /* Loop 2: the kernel number being applied */
3676  stage_loop, /* Loop 3: primitive loop for compound morphology */
3677  stage_limit, /* how many primitives are in this compound */
3678  kernel_loop, /* Loop 4: iterate the kernel over image */
3679  kernel_limit, /* number of times to iterate kernel */
3680  count, /* total count of primitive steps applied */
3681  kernel_changed, /* total count of changed using iterated kernel */
3682  method_changed; /* total count of changed over method iteration */
3683 
3684  ssize_t
3685  changed; /* number pixels changed by last primitive operation */
3686 
3687  char
3688  v_info[MagickPathExtent];
3689 
3690  assert(image != (Image *) NULL);
3691  assert(image->signature == MagickCoreSignature);
3692  assert(kernel != (KernelInfo *) NULL);
3693  assert(kernel->signature == MagickCoreSignature);
3694  assert(exception != (ExceptionInfo *) NULL);
3695  assert(exception->signature == MagickCoreSignature);
3696 
3697  count = 0; /* number of low-level morphology primitives performed */
3698  if ( iterations == 0 )
3699  return((Image *) NULL); /* null operation - nothing to do! */
3700 
3701  kernel_limit = (size_t) iterations;
3702  if ( iterations < 0 ) /* negative interations = infinite (well alomst) */
3703  kernel_limit = image->columns>image->rows ? image->columns : image->rows;
3704 
3705  verbose = IsStringTrue(GetImageArtifact(image,"debug"));
3706 
3707  /* initialise for cleanup */
3708  curr_image = (Image *) image;
3709  curr_compose = image->compose;
3710  (void) curr_compose;
3711  work_image = save_image = rslt_image = (Image *) NULL;
3712  reflected_kernel = (KernelInfo *) NULL;
3713 
3714  /* Initialize specific methods
3715  * + which loop should use the given iteratations
3716  * + how many primitives make up the compound morphology
3717  * + multi-kernel compose method to use (by default)
3718  */
3719  method_limit = 1; /* just do method once, unless otherwise set */
3720  stage_limit = 1; /* assume method is not a compound */
3721  special = MagickFalse; /* assume it is NOT a direct modify primitive */
3722  rslt_compose = compose; /* and we are composing multi-kernels as given */
3723  switch( method ) {
3724  case SmoothMorphology: /* 4 primitive compound morphology */
3725  stage_limit = 4;
3726  break;
3727  case OpenMorphology: /* 2 primitive compound morphology */
3729  case TopHatMorphology:
3730  case CloseMorphology:
3732  case BottomHatMorphology:
3733  case EdgeMorphology:
3734  stage_limit = 2;
3735  break;
3736  case HitAndMissMorphology:
3737  rslt_compose = LightenCompositeOp; /* Union of multi-kernel results */
3738  /* FALL THUR */
3739  case ThinningMorphology:
3740  case ThickenMorphology:
3741  method_limit = kernel_limit; /* iterate the whole method */
3742  kernel_limit = 1; /* do not do kernel iteration */
3743  break;
3744  case DistanceMorphology:
3745  case VoronoiMorphology:
3746  special = MagickTrue; /* use special direct primative */
3747  break;
3748  default:
3749  break;
3750  }
3751 
3752  /* Apply special methods with special requirments
3753  ** For example, single run only, or post-processing requirements
3754  */
3755  if ( special != MagickFalse )
3756  {
3757  rslt_image=CloneImage(image,0,0,MagickTrue,exception);
3758  if (rslt_image == (Image *) NULL)
3759  goto error_cleanup;
3760  if (SetImageStorageClass(rslt_image,DirectClass,exception) == MagickFalse)
3761  goto error_cleanup;
3762 
3763  changed=MorphologyPrimitiveDirect(rslt_image,method,kernel,exception);
3764 
3765  if (verbose != MagickFalse)
3766  (void) (void) FormatLocaleFile(stderr,
3767  "%s:%.20g.%.20g #%.20g => Changed %.20g\n",
3769  1.0,0.0,1.0, (double) changed);
3770 
3771  if ( changed < 0 )
3772  goto error_cleanup;
3773 
3774  if ( method == VoronoiMorphology ) {
3775  /* Preserve the alpha channel of input image - but turned it off */
3776  (void) SetImageAlphaChannel(rslt_image, DeactivateAlphaChannel,
3777  exception);
3778  (void) CompositeImage(rslt_image,image,CopyAlphaCompositeOp,
3779  MagickTrue,0,0,exception);
3780  (void) SetImageAlphaChannel(rslt_image, DeactivateAlphaChannel,
3781  exception);
3782  }
3783  goto exit_cleanup;
3784  }
3785 
3786  /* Handle user (caller) specified multi-kernel composition method */
3787  if ( compose != UndefinedCompositeOp )
3788  rslt_compose = compose; /* override default composition for method */
3789  if ( rslt_compose == UndefinedCompositeOp )
3790  rslt_compose = NoCompositeOp; /* still not defined! Then re-iterate */
3791 
3792  /* Some methods require a reflected kernel to use with primitives.
3793  * Create the reflected kernel for those methods. */
3794  switch ( method ) {
3795  case CorrelateMorphology:
3796  case CloseMorphology:
3798  case BottomHatMorphology:
3799  case SmoothMorphology:
3800  reflected_kernel = CloneKernelInfo(kernel);
3801  if (reflected_kernel == (KernelInfo *) NULL)
3802  goto error_cleanup;
3803  RotateKernelInfo(reflected_kernel,180);
3804  break;
3805  default:
3806  break;
3807  }
3808 
3809  /* Loops around more primitive morpholgy methods
3810  ** erose, dilate, open, close, smooth, edge, etc...
3811  */
3812  /* Loop 1: iterate the compound method */
3813  method_loop = 0;
3814  method_changed = 1;
3815  while ( method_loop < method_limit && method_changed > 0 ) {
3816  method_loop++;
3817  method_changed = 0;
3818 
3819  /* Loop 2: iterate over each kernel in a multi-kernel list */
3820  norm_kernel = (KernelInfo *) kernel;
3821  this_kernel = (KernelInfo *) kernel;
3822  rflt_kernel = reflected_kernel;
3823 
3824  kernel_number = 0;
3825  while ( norm_kernel != NULL ) {
3826 
3827  /* Loop 3: Compound Morphology Staging - Select Primative to apply */
3828  stage_loop = 0; /* the compound morphology stage number */
3829  while ( stage_loop < stage_limit ) {
3830  stage_loop++; /* The stage of the compound morphology */
3831 
3832  /* Select primitive morphology for this stage of compound method */
3833  this_kernel = norm_kernel; /* default use unreflected kernel */
3834  primitive = method; /* Assume method is a primitive */
3835  switch( method ) {
3836  case ErodeMorphology: /* just erode */
3837  case EdgeInMorphology: /* erode and image difference */
3838  primitive = ErodeMorphology;
3839  break;
3840  case DilateMorphology: /* just dilate */
3841  case EdgeOutMorphology: /* dilate and image difference */
3842  primitive = DilateMorphology;
3843  break;
3844  case OpenMorphology: /* erode then dialate */
3845  case TopHatMorphology: /* open and image difference */
3846  primitive = ErodeMorphology;
3847  if ( stage_loop == 2 )
3848  primitive = DilateMorphology;
3849  break;
3851  primitive = ErodeIntensityMorphology;
3852  if ( stage_loop == 2 )
3853  primitive = DilateIntensityMorphology;
3854  break;
3855  case CloseMorphology: /* dilate, then erode */
3856  case BottomHatMorphology: /* close and image difference */
3857  this_kernel = rflt_kernel; /* use the reflected kernel */
3858  primitive = DilateMorphology;
3859  if ( stage_loop == 2 )
3860  primitive = ErodeMorphology;
3861  break;
3863  this_kernel = rflt_kernel; /* use the reflected kernel */
3864  primitive = DilateIntensityMorphology;
3865  if ( stage_loop == 2 )
3866  primitive = ErodeIntensityMorphology;
3867  break;
3868  case SmoothMorphology: /* open, close */
3869  switch ( stage_loop ) {
3870  case 1: /* start an open method, which starts with Erode */
3871  primitive = ErodeMorphology;
3872  break;
3873  case 2: /* now Dilate the Erode */
3874  primitive = DilateMorphology;
3875  break;
3876  case 3: /* Reflect kernel a close */
3877  this_kernel = rflt_kernel; /* use the reflected kernel */
3878  primitive = DilateMorphology;
3879  break;
3880  case 4: /* Finish the Close */
3881  this_kernel = rflt_kernel; /* use the reflected kernel */
3882  primitive = ErodeMorphology;
3883  break;
3884  }
3885  break;
3886  case EdgeMorphology: /* dilate and erode difference */
3887  primitive = DilateMorphology;
3888  if ( stage_loop == 2 ) {
3889  save_image = curr_image; /* save the image difference */
3890  curr_image = (Image *) image;
3891  primitive = ErodeMorphology;
3892  }
3893  break;
3894  case CorrelateMorphology:
3895  /* A Correlation is a Convolution with a reflected kernel.
3896  ** However a Convolution is a weighted sum using a reflected
3897  ** kernel. It may seem stange to convert a Correlation into a
3898  ** Convolution as the Correlation is the simplier method, but
3899  ** Convolution is much more commonly used, and it makes sense to
3900  ** implement it directly so as to avoid the need to duplicate the
3901  ** kernel when it is not required (which is typically the
3902  ** default).
3903  */
3904  this_kernel = rflt_kernel; /* use the reflected kernel */
3905  primitive = ConvolveMorphology;
3906  break;
3907  default:
3908  break;
3909  }
3910  assert( this_kernel != (KernelInfo *) NULL );
3911 
3912  /* Extra information for debugging compound operations */
3913  if (verbose != MagickFalse) {
3914  if ( stage_limit > 1 )
3915  (void) FormatLocaleString(v_info,MagickPathExtent,"%s:%.20g.%.20g -> ",
3917  method_loop,(double) stage_loop);
3918  else if ( primitive != method )
3919  (void) FormatLocaleString(v_info, MagickPathExtent, "%s:%.20g -> ",
3921  method_loop);
3922  else
3923  v_info[0] = '\0';
3924  }
3925 
3926  /* Loop 4: Iterate the kernel with primitive */
3927  kernel_loop = 0;
3928  kernel_changed = 0;
3929  changed = 1;
3930  while ( kernel_loop < kernel_limit && changed > 0 ) {
3931  kernel_loop++; /* the iteration of this kernel */
3932 
3933  /* Create a clone as the destination image, if not yet defined */
3934  if ( work_image == (Image *) NULL )
3935  {
3936  work_image=CloneImage(image,0,0,MagickTrue,exception);
3937  if (work_image == (Image *) NULL)
3938  goto error_cleanup;
3939  if (SetImageStorageClass(work_image,DirectClass,exception) == MagickFalse)
3940  goto error_cleanup;
3941  }
3942 
3943  /* APPLY THE MORPHOLOGICAL PRIMITIVE (curr -> work) */
3944  count++;
3945  changed = MorphologyPrimitive(curr_image, work_image, primitive,
3946  this_kernel, bias, exception);
3947  if (verbose != MagickFalse) {
3948  if ( kernel_loop > 1 )
3949  (void) FormatLocaleFile(stderr, "\n"); /* add end-of-line from previous */
3950  (void) (void) FormatLocaleFile(stderr,
3951  "%s%s%s:%.20g.%.20g #%.20g => Changed %.20g",
3953  primitive),(this_kernel == rflt_kernel ) ? "*" : "",
3954  (double) (method_loop+kernel_loop-1),(double) kernel_number,
3955  (double) count,(double) changed);
3956  }
3957  if ( changed < 0 )
3958  goto error_cleanup;
3959  kernel_changed += changed;
3960  method_changed += changed;
3961 
3962  /* prepare next loop */
3963  { Image *tmp = work_image; /* swap images for iteration */
3964  work_image = curr_image;
3965  curr_image = tmp;
3966  }
3967  if ( work_image == image )
3968  work_image = (Image *) NULL; /* replace input 'image' */
3969 
3970  } /* End Loop 4: Iterate the kernel with primitive */
3971 
3972  if (verbose != MagickFalse && kernel_changed != (size_t)changed)
3973  (void) FormatLocaleFile(stderr, " Total %.20g",(double) kernel_changed);
3974  if (verbose != MagickFalse && stage_loop < stage_limit)
3975  (void) FormatLocaleFile(stderr, "\n"); /* add end-of-line before looping */
3976 
3977 #if 0
3978  (void) FormatLocaleFile(stderr, "--E-- image=0x%lx\n", (unsigned long)image);
3979  (void) FormatLocaleFile(stderr, " curr =0x%lx\n", (unsigned long)curr_image);
3980  (void) FormatLocaleFile(stderr, " work =0x%lx\n", (unsigned long)work_image);
3981  (void) FormatLocaleFile(stderr, " save =0x%lx\n", (unsigned long)save_image);
3982  (void) FormatLocaleFile(stderr, " union=0x%lx\n", (unsigned long)rslt_image);
3983 #endif
3984 
3985  } /* End Loop 3: Primative (staging) Loop for Coumpound Methods */
3986 
3987  /* Final Post-processing for some Compound Methods
3988  **
3989  ** The removal of any 'Sync' channel flag in the Image Compositon
3990  ** below ensures the methematical compose method is applied in a
3991  ** purely mathematical way, and only to the selected channels.
3992  ** Turn off SVG composition 'alpha blending'.
3993  */
3994  switch( method ) {
3995  case EdgeOutMorphology:
3996  case EdgeInMorphology:
3997  case TopHatMorphology:
3998  case BottomHatMorphology:
3999  if (verbose != MagickFalse)
4000  (void) FormatLocaleFile(stderr,
4001  "\n%s: Difference with original image",CommandOptionToMnemonic(
4002  MagickMorphologyOptions, method) );
4003  (void) CompositeImage(curr_image,image,DifferenceCompositeOp,
4004  MagickTrue,0,0,exception);
4005  break;
4006  case EdgeMorphology:
4007  if (verbose != MagickFalse)
4008  (void) FormatLocaleFile(stderr,
4009  "\n%s: Difference of Dilate and Erode",CommandOptionToMnemonic(
4010  MagickMorphologyOptions, method) );
4011  (void) CompositeImage(curr_image,save_image,DifferenceCompositeOp,
4012  MagickTrue,0,0,exception);
4013  save_image = DestroyImage(save_image); /* finished with save image */
4014  break;
4015  default:
4016  break;
4017  }
4018 
4019  /* multi-kernel handling: re-iterate, or compose results */
4020  if ( kernel->next == (KernelInfo *) NULL )
4021  rslt_image = curr_image; /* just return the resulting image */
4022  else if ( rslt_compose == NoCompositeOp )
4023  { if (verbose != MagickFalse) {
4024  if ( this_kernel->next != (KernelInfo *) NULL )
4025  (void) FormatLocaleFile(stderr, " (re-iterate)");
4026  else
4027  (void) FormatLocaleFile(stderr, " (done)");
4028  }
4029  rslt_image = curr_image; /* return result, and re-iterate */
4030  }
4031  else if ( rslt_image == (Image *) NULL)
4032  { if (verbose != MagickFalse)
4033  (void) FormatLocaleFile(stderr, " (save for compose)");
4034  rslt_image = curr_image;
4035  curr_image = (Image *) image; /* continue with original image */
4036  }
4037  else
4038  { /* Add the new 'current' result to the composition
4039  **
4040  ** The removal of any 'Sync' channel flag in the Image Compositon
4041  ** below ensures the methematical compose method is applied in a
4042  ** purely mathematical way, and only to the selected channels.
4043  ** IE: Turn off SVG composition 'alpha blending'.
4044  */
4045  if (verbose != MagickFalse)
4046  (void) FormatLocaleFile(stderr, " (compose \"%s\")",
4048  (void) CompositeImage(rslt_image,curr_image,rslt_compose,MagickTrue,
4049  0,0,exception);
4050  curr_image = DestroyImage(curr_image);
4051  curr_image = (Image *) image; /* continue with original image */
4052  }
4053  if (verbose != MagickFalse)
4054  (void) FormatLocaleFile(stderr, "\n");
4055 
4056  /* loop to the next kernel in a multi-kernel list */
4057  norm_kernel = norm_kernel->next;
4058  if ( rflt_kernel != (KernelInfo *) NULL )
4059  rflt_kernel = rflt_kernel->next;
4060  kernel_number++;
4061  } /* End Loop 2: Loop over each kernel */
4062 
4063  } /* End Loop 1: compound method interation */
4064 
4065  goto exit_cleanup;
4066 
4067  /* Yes goto's are bad, but it makes cleanup lot more efficient */
4068 error_cleanup:
4069  if ( curr_image == rslt_image )
4070  curr_image = (Image *) NULL;
4071  if ( rslt_image != (Image *) NULL )
4072  rslt_image = DestroyImage(rslt_image);
4073 exit_cleanup:
4074  if ( curr_image == rslt_image || curr_image == image )
4075  curr_image = (Image *) NULL;
4076  if ( curr_image != (Image *) NULL )
4077  curr_image = DestroyImage(curr_image);
4078  if ( work_image != (Image *) NULL )
4079  work_image = DestroyImage(work_image);
4080  if ( save_image != (Image *) NULL )
4081  save_image = DestroyImage(save_image);
4082  if ( reflected_kernel != (KernelInfo *) NULL )
4083  reflected_kernel = DestroyKernelInfo(reflected_kernel);
4084  return(rslt_image);
4085 }
4086 
4087 
4088 /*
4089 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4090 % %
4091 % %
4092 % %
4093 % M o r p h o l o g y I m a g e %
4094 % %
4095 % %
4096 % %
4097 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4098 %
4099 % MorphologyImage() applies a user supplied kernel to the image according to
4100 % the given mophology method.
4101 %
4102 % This function applies any and all user defined settings before calling
4103 % the above internal function MorphologyApply().
4104 %
4105 % User defined settings include...
4106 % * Output Bias for Convolution and correlation ("-define convolve:bias=??")
4107 % * Kernel Scale/normalize settings ("-define convolve:scale=??")
4108 % This can also includes the addition of a scaled unity kernel.
4109 % * Show Kernel being applied ("-define morphology:showKernel=1")
4110 %
4111 % Other operators that do not want user supplied options interfering,
4112 % especially "convolve:bias" and "morphology:showKernel" should use
4113 % MorphologyApply() directly.
4114 %
4115 % The format of the MorphologyImage method is:
4116 %
4117 % Image *MorphologyImage(const Image *image,MorphologyMethod method,
4118 % const ssize_t iterations,KernelInfo *kernel,ExceptionInfo *exception)
4119 %
4120 % A description of each parameter follows:
4121 %
4122 % o image: the image.
4123 %
4124 % o method: the morphology method to be applied.
4125 %
4126 % o iterations: apply the operation this many times (or no change).
4127 % A value of -1 means loop until no change found.
4128 % How this is applied may depend on the morphology method.
4129 % Typically this is a value of 1.
4130 %
4131 % o kernel: An array of double representing the morphology kernel.
4132 % Warning: kernel may be normalized for the Convolve method.
4133 %
4134 % o exception: return any errors or warnings in this structure.
4135 %
4136 */
4138  const MorphologyMethod method,const ssize_t iterations,
4139  const KernelInfo *kernel,ExceptionInfo *exception)
4140 {
4141  const char
4142  *artifact;
4143 
4145  compose;
4146 
4147  double
4148  bias;
4149 
4150  Image
4151  *morphology_image;
4152 
4153  KernelInfo
4154  *curr_kernel;
4155 
4156  curr_kernel = (KernelInfo *) kernel;
4157  bias=0.0;
4158  compose = UndefinedCompositeOp; /* use default for method */
4159 
4160  /* Apply Convolve/Correlate Normalization and Scaling Factors.
4161  * This is done BEFORE the ShowKernelInfo() function is called so that
4162  * users can see the results of the 'option:convolve:scale' option.
4163  */
4164  if ( method == ConvolveMorphology || method == CorrelateMorphology ) {
4165  /* Get the bias value as it will be needed */
4166  artifact = GetImageArtifact(image,"convolve:bias");
4167  if ( artifact != (const char *) NULL) {
4168  if (IsGeometry(artifact) == MagickFalse)
4169  (void) ThrowMagickException(exception,GetMagickModule(),
4170  OptionWarning,"InvalidSetting","'%s' '%s'",
4171  "convolve:bias",artifact);
4172  else
4173  bias=StringToDoubleInterval(artifact,(double) QuantumRange+1.0);
4174  }
4175 
4176  /* Scale kernel according to user wishes */
4177  artifact = GetImageArtifact(image,"convolve:scale");
4178  if ( artifact != (const char *) NULL ) {
4179  if (IsGeometry(artifact) == MagickFalse)
4180  (void) ThrowMagickException(exception,GetMagickModule(),
4181  OptionWarning,"InvalidSetting","'%s' '%s'",
4182  "convolve:scale",artifact);
4183  else {
4184  if ( curr_kernel == kernel )
4185  curr_kernel = CloneKernelInfo(kernel);
4186  if (curr_kernel == (KernelInfo *) NULL)
4187  return((Image *) NULL);
4188  ScaleGeometryKernelInfo(curr_kernel, artifact);
4189  }
4190  }
4191  }
4192 
4193  /* display the (normalized) kernel via stderr */
4194  artifact=GetImageArtifact(image,"morphology:showKernel");
4195  if (IsStringTrue(artifact) != MagickFalse)
4196  ShowKernelInfo(curr_kernel);
4197 
4198  /* Override the default handling of multi-kernel morphology results
4199  * If 'Undefined' use the default method
4200  * If 'None' (default for 'Convolve') re-iterate previous result
4201  * Otherwise merge resulting images using compose method given.
4202  * Default for 'HitAndMiss' is 'Lighten'.
4203  */
4204  {
4205  ssize_t
4206  parse;
4207 
4208  artifact = GetImageArtifact(image,"morphology:compose");
4209  if ( artifact != (const char *) NULL) {
4211  MagickFalse,artifact);
4212  if ( parse < 0 )
4213  (void) ThrowMagickException(exception,GetMagickModule(),
4214  OptionWarning,"UnrecognizedComposeOperator","'%s' '%s'",
4215  "morphology:compose",artifact);
4216  else
4217  compose=(CompositeOperator)parse;
4218  }
4219  }
4220  /* Apply the Morphology */
4221  morphology_image = MorphologyApply(image,method,iterations,
4222  curr_kernel,compose,bias,exception);
4223 
4224  /* Cleanup and Exit */
4225  if ( curr_kernel != kernel )
4226  curr_kernel=DestroyKernelInfo(curr_kernel);
4227  return(morphology_image);
4228 }
4229 
4230 /*
4231 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4232 % %
4233 % %
4234 % %
4235 + R o t a t e K e r n e l I n f o %
4236 % %
4237 % %
4238 % %
4239 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4240 %
4241 % RotateKernelInfo() rotates the kernel by the angle given.
4242 %
4243 % Currently it is restricted to 90 degree angles, of either 1D kernels
4244 % or square kernels. And 'circular' rotations of 45 degrees for 3x3 kernels.
4245 % It will ignore usless rotations for specific 'named' built-in kernels.
4246 %
4247 % The format of the RotateKernelInfo method is:
4248 %
4249 % void RotateKernelInfo(KernelInfo *kernel, double angle)
4250 %
4251 % A description of each parameter follows:
4252 %
4253 % o kernel: the Morphology/Convolution kernel
4254 %
4255 % o angle: angle to rotate in degrees
4256 %
4257 % This function is currently internal to this module only, but can be exported
4258 % to other modules if needed.
4259 */
4260 static void RotateKernelInfo(KernelInfo *kernel, double angle)
4261 {
4262  /* angle the lower kernels first */
4263  if ( kernel->next != (KernelInfo *) NULL)
4264  RotateKernelInfo(kernel->next, angle);
4265 
4266  /* WARNING: Currently assumes the kernel (rightly) is horizontally symetrical
4267  **
4268  ** TODO: expand beyond simple 90 degree rotates, flips and flops
4269  */
4270 
4271  /* Modulus the angle */
4272  angle = fmod(angle, 360.0);
4273  if ( angle < 0 )
4274  angle += 360.0;
4275 
4276  if ( 337.5 < angle || angle <= 22.5 )
4277  return; /* Near zero angle - no change! - At least not at this time */
4278 
4279  /* Handle special cases */
4280  switch (kernel->type) {
4281  /* These built-in kernels are cylindrical kernels, rotating is useless */
4282  case GaussianKernel:
4283  case DoGKernel:
4284  case LoGKernel:
4285  case DiskKernel:
4286  case PeaksKernel:
4287  case LaplacianKernel:
4288  case ChebyshevKernel:
4289  case ManhattanKernel:
4290  case EuclideanKernel:
4291  return;
4292 
4293  /* These may be rotatable at non-90 angles in the future */
4294  /* but simply rotating them in multiples of 90 degrees is useless */
4295  case SquareKernel:
4296  case DiamondKernel:
4297  case PlusKernel:
4298  case CrossKernel:
4299  return;
4300 
4301  /* These only allows a +/-90 degree rotation (by transpose) */
4302  /* A 180 degree rotation is useless */
4303  case BlurKernel:
4304  if ( 135.0 < angle && angle <= 225.0 )
4305  return;
4306  if ( 225.0 < angle && angle <= 315.0 )
4307  angle -= 180;
4308  break;
4309 
4310  default:
4311  break;
4312  }
4313  /* Attempt rotations by 45 degrees -- 3x3 kernels only */
4314  if ( 22.5 < fmod(angle,90.0) && fmod(angle,90.0) <= 67.5 )
4315  {
4316  if ( kernel->width == 3 && kernel->height == 3 )
4317  { /* Rotate a 3x3 square by 45 degree angle */
4318  double t = kernel->values[0];
4319  kernel->values[0] = kernel->values[3];
4320  kernel->values[3] = kernel->values[6];
4321  kernel->values[6] = kernel->values[7];
4322  kernel->values[7] = kernel->values[8];
4323  kernel->values[8] = kernel->values[5];
4324  kernel->values[5] = kernel->values[2];
4325  kernel->values[2] = kernel->values[1];
4326  kernel->values[1] = t;
4327  /* rotate non-centered origin */
4328  if ( kernel->x != 1 || kernel->y != 1 ) {
4329  ssize_t x,y;
4330  x = (ssize_t) kernel->x-1;
4331  y = (ssize_t) kernel->y-1;
4332  if ( x == y ) x = 0;
4333  else if ( x == 0 ) x = -y;
4334  else if ( x == -y ) y = 0;
4335  else if ( y == 0 ) y = x;
4336  kernel->x = (ssize_t) x+1;
4337  kernel->y = (ssize_t) y+1;
4338  }
4339  angle = fmod(angle+315.0, 360.0); /* angle reduced 45 degrees */
4340  kernel->angle = fmod(kernel->angle+45.0, 360.0);
4341  }
4342  else
4343  perror("Unable to rotate non-3x3 kernel by 45 degrees");
4344  }
4345  if ( 45.0 < fmod(angle, 180.0) && fmod(angle,180.0) <= 135.0 )
4346  {
4347  if ( kernel->width == 1 || kernel->height == 1 )
4348  { /* Do a transpose of a 1 dimensional kernel,
4349  ** which results in a fast 90 degree rotation of some type.
4350  */
4351  ssize_t
4352  t;
4353  t = (ssize_t) kernel->width;
4354  kernel->width = kernel->height;
4355  kernel->height = (size_t) t;
4356  t = kernel->x;
4357  kernel->x = kernel->y;
4358  kernel->y = t;
4359  if ( kernel->width == 1 ) {
4360  angle = fmod(angle+270.0, 360.0); /* angle reduced 90 degrees */
4361  kernel->angle = fmod(kernel->angle+90.0, 360.0);
4362  } else {
4363  angle = fmod(angle+90.0, 360.0); /* angle increased 90 degrees */
4364  kernel->angle = fmod(kernel->angle+270.0, 360.0);
4365  }
4366  }
4367  else if ( kernel->width == kernel->height )
4368  { /* Rotate a square array of values by 90 degrees */
4369  { ssize_t
4370  i,j,x,y;
4371 
4373  *k,t;
4374 
4375  k=kernel->values;
4376  for( i=0, x=(ssize_t) kernel->width-1; i<=x; i++, x--)
4377  for( j=0, y=(ssize_t) kernel->height-1; j<y; j++, y--)
4378  { t = k[i+j*kernel->width];
4379  k[i+j*kernel->width] = k[j+x*kernel->width];
4380  k[j+x*kernel->width] = k[x+y*kernel->width];
4381  k[x+y*kernel->width] = k[y+i*kernel->width];
4382  k[y+i*kernel->width] = t;
4383  }
4384  }
4385  /* rotate the origin - relative to center of array */
4386  { ssize_t x,y;
4387  x = (ssize_t) (kernel->x*2-kernel->width+1);
4388  y = (ssize_t) (kernel->y*2-kernel->height+1);
4389  kernel->x = (ssize_t) ( -y +(ssize_t) kernel->width-1)/2;
4390  kernel->y = (ssize_t) ( +x +(ssize_t) kernel->height-1)/2;
4391  }
4392  angle = fmod(angle+270.0, 360.0); /* angle reduced 90 degrees */
4393  kernel->angle = fmod(kernel->angle+90.0, 360.0);
4394  }
4395  else
4396  perror("Unable to rotate a non-square, non-linear kernel 90 degrees");
4397  }
4398  if ( 135.0 < angle && angle <= 225.0 )
4399  {
4400  /* For a 180 degree rotation - also know as a reflection
4401  * This is actually a very very common operation!
4402  * Basically all that is needed is a reversal of the kernel data!
4403  * And a reflection of the origon
4404  */
4406  t;
4407 
4409  *k;
4410 
4411  ssize_t
4412  i,
4413  j;
4414 
4415  k=kernel->values;
4416  j=(ssize_t) (kernel->width*kernel->height-1);
4417  for (i=0; i < j; i++, j--)
4418  t=k[i], k[i]=k[j], k[j]=t;
4419 
4420  kernel->x = (ssize_t) kernel->width - kernel->x - 1;
4421  kernel->y = (ssize_t) kernel->height - kernel->y - 1;
4422  angle = fmod(angle-180.0, 360.0); /* angle+180 degrees */
4423  kernel->angle = fmod(kernel->angle+180.0, 360.0);
4424  }
4425  /* At this point angle should at least between -45 (315) and +45 degrees
4426  * In the future some form of non-orthogonal angled rotates could be
4427  * performed here, posibily with a linear kernel restriction.
4428  */
4429 
4430  return;
4431 }
4432 
4433 /*
4434 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4435 % %
4436 % %
4437 % %
4438 % S c a l e G e o m e t r y K e r n e l I n f o %
4439 % %
4440 % %
4441 % %
4442 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4443 %
4444 % ScaleGeometryKernelInfo() takes a geometry argument string, typically
4445 % provided as a "-set option:convolve:scale {geometry}" user setting,
4446 % and modifies the kernel according to the parsed arguments of that setting.
4447 %
4448 % The first argument (and any normalization flags) are passed to
4449 % ScaleKernelInfo() to scale/normalize the kernel. The second argument
4450 % is then passed to UnityAddKernelInfo() to add a scled unity kernel
4451 % into the scaled/normalized kernel.
4452 %
4453 % The format of the ScaleGeometryKernelInfo method is:
4454 %
4455 % void ScaleGeometryKernelInfo(KernelInfo *kernel,
4456 % const double scaling_factor,const MagickStatusType normalize_flags)
4457 %
4458 % A description of each parameter follows:
4459 %
4460 % o kernel: the Morphology/Convolution kernel to modify
4461 %
4462 % o geometry:
4463 % The geometry string to parse, typically from the user provided
4464 % "-set option:convolve:scale {geometry}" setting.
4465 %
4466 */
4468  const char *geometry)
4469 {
4471  flags;
4472 
4473  GeometryInfo
4474  args;
4475 
4476  SetGeometryInfo(&args);
4477  flags = ParseGeometry(geometry, &args);
4478 
4479 #if 0
4480  /* For Debugging Geometry Input */
4481  (void) FormatLocaleFile(stderr, "Geometry = 0x%04X : %lg x %lg %+lg %+lg\n",
4482  flags, args.rho, args.sigma, args.xi, args.psi );
4483 #endif
4484 
4485  if ( (flags & PercentValue) != 0 ) /* Handle Percentage flag*/
4486  args.rho *= 0.01, args.sigma *= 0.01;
4487 
4488  if ( (flags & RhoValue) == 0 ) /* Set Defaults for missing args */
4489  args.rho = 1.0;
4490  if ( (flags & SigmaValue) == 0 )
4491  args.sigma = 0.0;
4492 
4493  /* Scale/Normalize the input kernel */
4494  ScaleKernelInfo(kernel, args.rho, (GeometryFlags) flags);
4495 
4496  /* Add Unity Kernel, for blending with original */
4497  if ( (flags & SigmaValue) != 0 )
4498  UnityAddKernelInfo(kernel, args.sigma);
4499 
4500  return;
4501 }
4502 /*
4503 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4504 % %
4505 % %
4506 % %
4507 % S c a l e K e r n e l I n f o %
4508 % %
4509 % %
4510 % %
4511 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4512 %
4513 % ScaleKernelInfo() scales the given kernel list by the given amount, with or
4514 % without normalization of the sum of the kernel values (as per given flags).
4515 %
4516 % By default (no flags given) the values within the kernel is scaled
4517 % directly using given scaling factor without change.
4518 %
4519 % If either of the two 'normalize_flags' are given the kernel will first be
4520 % normalized and then further scaled by the scaling factor value given.
4521 %
4522 % Kernel normalization ('normalize_flags' given) is designed to ensure that
4523 % any use of the kernel scaling factor with 'Convolve' or 'Correlate'
4524 % morphology methods will fall into -1.0 to +1.0 range. Note that for
4525 % non-HDRI versions of IM this may cause images to have any negative results
4526 % clipped, unless some 'bias' is used.
4527 %
4528 % More specifically. Kernels which only contain positive values (such as a
4529 % 'Gaussian' kernel) will be scaled so that those values sum to +1.0,
4530 % ensuring a 0.0 to +1.0 output range for non-HDRI images.
4531 %
4532 % For Kernels that contain some negative values, (such as 'Sharpen' kernels)
4533 % the kernel will be scaled by the absolute of the sum of kernel values, so
4534 % that it will generally fall within the +/- 1.0 range.
4535 %
4536 % For kernels whose values sum to zero, (such as 'Laplician' kernels) kernel
4537 % will be scaled by just the sum of the postive values, so that its output
4538 % range will again fall into the +/- 1.0 range.
4539 %
4540 % For special kernels designed for locating shapes using 'Correlate', (often
4541 % only containing +1 and -1 values, representing foreground/brackground
4542 % matching) a special normalization method is provided to scale the positive
4543 % values separately to those of the negative values, so the kernel will be
4544 % forced to become a zero-sum kernel better suited to such searches.
4545 %
4546 % WARNING: Correct normalization of the kernel assumes that the '*_range'
4547 % attributes within the kernel structure have been correctly set during the
4548 % kernels creation.
4549 %
4550 % NOTE: The values used for 'normalize_flags' have been selected specifically
4551 % to match the use of geometry options, so that '!' means NormalizeValue, '^'
4552 % means CorrelateNormalizeValue. All other GeometryFlags values are ignored.
4553 %
4554 % The format of the ScaleKernelInfo method is:
4555 %
4556 % void ScaleKernelInfo(KernelInfo *kernel, const double scaling_factor,
4557 % const MagickStatusType normalize_flags )
4558 %
4559 % A description of each parameter follows:
4560 %
4561 % o kernel: the Morphology/Convolution kernel
4562 %
4563 % o scaling_factor:
4564 % multiply all values (after normalization) by this factor if not
4565 % zero. If the kernel is normalized regardless of any flags.
4566 %
4567 % o normalize_flags:
4568 % GeometryFlags defining normalization method to use.
4569 % specifically: NormalizeValue, CorrelateNormalizeValue,
4570 % and/or PercentValue
4571 %
4572 */
4574  const double scaling_factor,const GeometryFlags normalize_flags)
4575 {
4576  double
4577  pos_scale,
4578  neg_scale;
4579 
4580  ssize_t
4581  i;
4582 
4583  /* do the other kernels in a multi-kernel list first */
4584  if ( kernel->next != (KernelInfo *) NULL)
4585  ScaleKernelInfo(kernel->next, scaling_factor, normalize_flags);
4586 
4587  /* Normalization of Kernel */
4588  pos_scale = 1.0;
4589  if ( (normalize_flags&NormalizeValue) != 0 ) {
4590  if ( fabs(kernel->positive_range + kernel->negative_range) >= MagickEpsilon )
4591  /* non-zero-summing kernel (generally positive) */
4592  pos_scale = fabs(kernel->positive_range + kernel->negative_range);
4593  else
4594  /* zero-summing kernel */
4595  pos_scale = kernel->positive_range;
4596  }
4597  /* Force kernel into a normalized zero-summing kernel */
4598  if ( (normalize_flags&CorrelateNormalizeValue) != 0 ) {
4599  pos_scale = ( fabs(kernel->positive_range) >= MagickEpsilon )
4600  ? kernel->positive_range : 1.0;
4601  neg_scale = ( fabs(kernel->negative_range) >= MagickEpsilon )
4602  ? -kernel->negative_range : 1.0;
4603  }
4604  else
4605  neg_scale = pos_scale;
4606 
4607  /* finialize scaling_factor for positive and negative components */
4608  pos_scale = scaling_factor/pos_scale;
4609  neg_scale = scaling_factor/neg_scale;
4610 
4611  for (i=0; i < (ssize_t) (kernel->width*kernel->height); i++)
4612  if (!IsNaN(kernel->values[i]))
4613  kernel->values[i] *= (kernel->values[i] >= 0) ? pos_scale : neg_scale;
4614 
4615  /* convolution output range */
4616  kernel->positive_range *= pos_scale;
4617  kernel->negative_range *= neg_scale;
4618  /* maximum and minimum values in kernel */
4619  kernel->maximum *= (kernel->maximum >= 0.0) ? pos_scale : neg_scale;
4620  kernel->minimum *= (kernel->minimum >= 0.0) ? pos_scale : neg_scale;
4621 
4622  /* swap kernel settings if user's scaling factor is negative */
4623  if ( scaling_factor < MagickEpsilon ) {
4624  double t;
4625  t = kernel->positive_range;
4626  kernel->positive_range = kernel->negative_range;
4627  kernel->negative_range = t;
4628  t = kernel->maximum;
4629  kernel->maximum = kernel->minimum;
4630  kernel->minimum = 1;
4631  }
4632 
4633  return;
4634 }
4635 
4636 /*
4637 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4638 % %
4639 % %
4640 % %
4641 % S h o w K e r n e l I n f o %
4642 % %
4643 % %
4644 % %
4645 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4646 %
4647 % ShowKernelInfo() outputs the details of the given kernel defination to
4648 % standard error, generally due to a users 'morphology:showKernel' option
4649 % request.
4650 %
4651 % The format of the ShowKernel method is:
4652 %
4653 % void ShowKernelInfo(const KernelInfo *kernel)
4654 %
4655 % A description of each parameter follows:
4656 %
4657 % o kernel: the Morphology/Convolution kernel
4658 %
4659 */
4661 {
4662  const KernelInfo
4663  *k;
4664 
4665  size_t
4666  c, i, u, v;
4667 
4668  for (c=0, k=kernel; k != (KernelInfo *) NULL; c++, k=k->next ) {
4669 
4670  (void) FormatLocaleFile(stderr, "Kernel");
4671  if ( kernel->next != (KernelInfo *) NULL )
4672  (void) FormatLocaleFile(stderr, " #%lu", (unsigned long) c );
4673  (void) FormatLocaleFile(stderr, " \"%s",
4675  if ( fabs(k->angle) >= MagickEpsilon )
4676  (void) FormatLocaleFile(stderr, "@%lg", k->angle);
4677  (void) FormatLocaleFile(stderr, "\" of size %lux%lu%+ld%+ld",(unsigned long)
4678  k->width,(unsigned long) k->height,(long) k->x,(long) k->y);
4679  (void) FormatLocaleFile(stderr,
4680  " with values from %.*lg to %.*lg\n",
4681  GetMagickPrecision(), k->minimum,
4682  GetMagickPrecision(), k->maximum);
4683  (void) FormatLocaleFile(stderr, "Forming a output range from %.*lg to %.*lg",
4684  GetMagickPrecision(), k->negative_range,
4685  GetMagickPrecision(), k->positive_range);
4686  if ( fabs(k->positive_range+k->negative_range) < MagickEpsilon )
4687  (void) FormatLocaleFile(stderr, " (Zero-Summing)\n");
4688  else if ( fabs(k->positive_range+k->negative_range-1.0) < MagickEpsilon )
4689  (void) FormatLocaleFile(stderr, " (Normalized)\n");
4690  else
4691  (void) FormatLocaleFile(stderr, " (Sum %.*lg)\n",
4692  GetMagickPrecision(), k->positive_range+k->negative_range);
4693  for (i=v=0; v < k->height; v++) {
4694  (void) FormatLocaleFile(stderr, "%2lu:", (unsigned long) v );
4695  for (u=0; u < k->width; u++, i++)
4696  if (IsNaN(k->values[i]))
4697  (void) FormatLocaleFile(stderr," %*s", GetMagickPrecision()+3, "nan");
4698  else
4699  (void) FormatLocaleFile(stderr," %*.*lg", GetMagickPrecision()+3,
4700  GetMagickPrecision(), (double) k->values[i]);
4701  (void) FormatLocaleFile(stderr,"\n");
4702  }
4703  }
4704 }
4705 
4706 /*
4707 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4708 % %
4709 % %
4710 % %
4711 % U n i t y A d d K e r n a l I n f o %
4712 % %
4713 % %
4714 % %
4715 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4716 %
4717 % UnityAddKernelInfo() Adds a given amount of the 'Unity' Convolution Kernel
4718 % to the given pre-scaled and normalized Kernel. This in effect adds that
4719 % amount of the original image into the resulting convolution kernel. This
4720 % value is usually provided by the user as a percentage value in the
4721 % 'convolve:scale' setting.
4722 %
4723 % The resulting effect is to convert the defined kernels into blended
4724 % soft-blurs, unsharp kernels or into sharpening kernels.
4725 %
4726 % The format of the UnityAdditionKernelInfo method is:
4727 %
4728 % void UnityAdditionKernelInfo(KernelInfo *kernel, const double scale )
4729 %
4730 % A description of each parameter follows:
4731 %
4732 % o kernel: the Morphology/Convolution kernel
4733 %
4734 % o scale:
4735 % scaling factor for the unity kernel to be added to
4736 % the given kernel.
4737 %
4738 */
4740  const double scale)
4741 {
4742  /* do the other kernels in a multi-kernel list first */
4743  if ( kernel->next != (KernelInfo *) NULL)
4744  UnityAddKernelInfo(kernel->next, scale);
4745 
4746  /* Add the scaled unity kernel to the existing kernel */
4747  kernel->values[kernel->x+kernel->y*kernel->width] += scale;
4748  CalcKernelMetaData(kernel); /* recalculate the meta-data */
4749 
4750  return;
4751 }
4752 
4753 /*
4754 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4755 % %
4756 % %
4757 % %
4758 % Z e r o K e r n e l N a n s %
4759 % %
4760 % %
4761 % %
4762 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4763 %
4764 % ZeroKernelNans() replaces any special 'nan' value that may be present in
4765 % the kernel with a zero value. This is typically done when the kernel will
4766 % be used in special hardware (GPU) convolution processors, to simply
4767 % matters.
4768 %
4769 % The format of the ZeroKernelNans method is:
4770 %
4771 % void ZeroKernelNans (KernelInfo *kernel)
4772 %
4773 % A description of each parameter follows:
4774 %
4775 % o kernel: the Morphology/Convolution kernel
4776 %
4777 */
4779 {
4780  size_t
4781  i;
4782 
4783  /* do the other kernels in a multi-kernel list first */
4784  if (kernel->next != (KernelInfo *) NULL)
4785  ZeroKernelNans(kernel->next);
4786 
4787  for (i=0; i < (kernel->width*kernel->height); i++)
4788  if (IsNaN(kernel->values[i]))
4789  kernel->values[i]=0.0;
4790 
4791  return;
4792 }
double psi
Definition: geometry.h:108
struct _KernelInfo * next
Definition: morphology.h:125
size_t rows
Definition: image.h:172
MagickPrivate Image * MorphologyApply(const Image *image, const MorphologyMethod method, const ssize_t iterations, const KernelInfo *kernel, const CompositeOperator compose, const double bias, ExceptionInfo *exception)
Definition: morphology.c:3642
#define magick_restrict
Definition: MagickCore.h:41
MagickDoubleType MagickRealType
Definition: magick-type.h:124
MagickExport CacheView * DestroyCacheView(CacheView *cache_view)
Definition: cache-view.c:252
static void ExpandMirrorKernelInfo(KernelInfo *)
Definition: morphology.c:2328
MagickProgressMonitor progress_monitor
Definition: image.h:303
ImageType type
Definition: image.h:264
static KernelInfo * LastKernelInfo(KernelInfo *kernel)
Definition: morphology.c:118
static Quantum GetPixelAlpha(const Image *magick_restrict image, const Quantum *magick_restrict pixel)
#define DisableMSCWarning(nr)
Definition: studio.h:347
#define MagickAssumeAligned(address)
ssize_t y
Definition: geometry.h:118
double positive_range
Definition: morphology.h:119
MagickExport ssize_t ParseCommandOption(const CommandOption option, const MagickBooleanType list, const char *options)
Definition: option.c:3077
size_t height
Definition: morphology.h:108
MagickExport KernelInfo * DestroyKernelInfo(KernelInfo *kernel)
Definition: morphology.c:2268
#define ThrowFatalException(severity, tag)
size_t signature
Definition: exception.h:123
static size_t GetOpenMPMaximumThreads(void)
MagickExport Image * MorphologyImage(const Image *image, const MorphologyMethod method, const ssize_t iterations, const KernelInfo *kernel, ExceptionInfo *exception)
Definition: morphology.c:4137
double rho
Definition: geometry.h:108
MagickExport void SetGeometryInfo(GeometryInfo *geometry_info)
Definition: geometry.c:1748
double negative_range
Definition: morphology.h:119
static ssize_t MorphologyPrimitive(const Image *image, Image *morphology_image, const MorphologyMethod method, const KernelInfo *kernel, const double bias, ExceptionInfo *exception)
Definition: morphology.c:2562
MagickExport const char * GetImageArtifact(const Image *image, const char *artifact)
Definition: artifact.c:273
static ssize_t MorphologyPrimitiveDirect(Image *image, const MorphologyMethod method, const KernelInfo *kernel, ExceptionInfo *exception)
Definition: morphology.c:3250
#define Minimize(assign, value)
Definition: morphology.c:91
ssize_t x
Definition: morphology.h:112
static PixelTrait GetPixelChannelTraits(const Image *magick_restrict image, const PixelChannel channel)
#define MagickPI
Definition: image-private.h:42
MagickExport ssize_t FormatLocaleString(char *magick_restrict string, const size_t length, const char *magick_restrict format,...)
Definition: locale.c:465
MagickPrivate size_t GetOptimalKernelWidth1D(const double, const double)
MagickExport const Quantum * GetCacheViewVirtualPixels(const CacheView *cache_view, const ssize_t x, const ssize_t y, const size_t columns, const size_t rows, ExceptionInfo *exception)
Definition: cache-view.c:651
MagickExport void ScaleGeometryKernelInfo(KernelInfo *kernel, const char *geometry)
Definition: morphology.c:4467
size_t signature
Definition: morphology.h:129
MagickExport void ScaleKernelInfo(KernelInfo *kernel, const double scaling_factor, const GeometryFlags normalize_flags)
Definition: morphology.c:4573
#define MagickSQ2
Definition: image-private.h:44
#define MagickEpsilon
Definition: magick-type.h:114
double sigma
Definition: geometry.h:108
MorphologyMethod
Definition: morphology.h:69
static KernelInfo * ParseKernelArray(const char *kernel_string)
Definition: morphology.c:213
MagickExport MagickBooleanType CompositeImage(Image *image, const Image *composite, const CompositeOperator compose, const MagickBooleanType clip_to_self, const ssize_t x_offset, const ssize_t y_offset, ExceptionInfo *exception)
Definition: composite.c:1525
#define Maximize(assign, value)
Definition: morphology.c:92
MagickExport char * FileToString(const char *filename, const size_t extent, ExceptionInfo *exception)
Definition: string.c:965
ssize_t MagickOffsetType
Definition: magick-type.h:133
static Quantum ClampToQuantum(const MagickRealType quantum)
Definition: quantum.h:85
KernelInfoType type
Definition: morphology.h:105
Definition: image.h:151
double maximum
Definition: morphology.h:119
MagickExport KernelInfo * AcquireKernelInfo(const char *kernel_string, ExceptionInfo *exception)
Definition: morphology.c:485
#define MagickCoreSignature
MagickExport Quantum * GetCacheViewAuthenticPixels(CacheView *cache_view, const ssize_t x, const ssize_t y, const size_t columns, const size_t rows, ExceptionInfo *exception)
Definition: cache-view.c:299
MagickExport KernelInfo * AcquireKernelBuiltIn(const KernelInfoType type, const GeometryInfo *args, ExceptionInfo *exception)
Definition: morphology.c:950
MagickPrivate void ShowKernelInfo(const KernelInfo *kernel)
Definition: morphology.c:4660
MagickExport MagickBooleanType IsGeometry(const char *geometry)
Definition: geometry.c:618
static KernelInfo * ParseKernelName(const char *kernel_string, ExceptionInfo *exception)
Definition: morphology.c:372
MagickExport ssize_t FormatLocaleFile(FILE *file, const char *magick_restrict format,...)
Definition: locale.c:370
MagickExport MagickBooleanType SetImageAlphaChannel(Image *image, const AlphaChannelOption alpha_type, ExceptionInfo *exception)
Definition: channel.c:973
MagickBooleanType
Definition: magick-type.h:161
unsigned int MagickStatusType
Definition: magick-type.h:125
static double PerceptibleReciprocal(const double x)
MagickExport const char * CommandOptionToMnemonic(const CommandOption option, const ssize_t type)
Definition: option.c:2786
#define Magick2PI
Definition: image-private.h:36
MagickExport void * AcquireQuantumMemory(const size_t count, const size_t quantum)
Definition: memory.c:665
MagickPrivate size_t GetOptimalKernelWidth2D(const double, const double)
Definition: gem.c:1684
MagickExport magick_hot_spot size_t GetNextToken(const char *magick_restrict start, const char **magick_restrict end, const size_t extent, char *magick_restrict token)
Definition: token.c:174
static int GetOpenMPThreadId(void)
#define MagickSQ2PI
Definition: image-private.h:45
#define RestoreMSCWarning
Definition: studio.h:348
static size_t fact(size_t n)
Definition: morphology.c:96
#define MagickPathExtent
MagickExport void * RelinquishAlignedMemory(void *memory)
Definition: memory.c:1120
MagickExport MagickBooleanType IsStringTrue(const char *value)
Definition: string.c:1386
static void CalcKernelMetaData(KernelInfo *)
Definition: morphology.c:2481
PixelTrait alpha_trait
Definition: image.h:280
MagickExport int GetMagickPrecision(void)
Definition: magick.c:942
#define MagickMaximumValue
Definition: magick-type.h:115
double minimum
Definition: morphology.h:119
MagickExport MagickBooleanType ThrowMagickException(ExceptionInfo *exception, const char *module, const char *function, const size_t line, const ExceptionType severity, const char *tag, const char *format,...)
Definition: exception.c:1145
size_t width
Definition: morphology.h:108
size_t signature
Definition: image.h:354
#define QuantumScale
Definition: magick-type.h:119
size_t columns
Definition: image.h:172
MagickBooleanType(* MagickProgressMonitor)(const char *, const MagickOffsetType, const MagickSizeType, void *)
Definition: monitor.h:26
double angle
Definition: morphology.h:119
MagickExport MagickBooleanType SetImageStorageClass(Image *image, const ClassType storage_class, ExceptionInfo *exception)
Definition: image.c:2616
PixelChannel
Definition: pixel.h:70
MagickExport void * AcquireAlignedMemory(const size_t count, const size_t quantum)
Definition: memory.c:365
#define MagickMax(x, y)
Definition: image-private.h:38
GeometryFlags
Definition: geometry.h:25
static size_t GetPixelChannels(const Image *magick_restrict image)
MagickExport int LocaleCompare(const char *p, const char *q)
Definition: locale.c:1401
#define IsNaN(a)
Definition: magick-type.h:184
MagickPrivate void ZeroKernelNans(KernelInfo *kernel)
Definition: morphology.c:4778
#define GetMagickModule()
Definition: log.h:28
static PixelChannel GetPixelChannelChannel(const Image *magick_restrict image, const ssize_t offset)
MagickExport CacheView * AcquireVirtualCacheView(const Image *image, ExceptionInfo *exception)
Definition: cache-view.c:149
static void RotateKernelInfo(KernelInfo *, double)
Definition: morphology.c:4260
static double StringToDoubleInterval(const char *string, const double interval)
static MagickBooleanType SameKernelInfo(const KernelInfo *kernel1, const KernelInfo *kernel2)
Definition: morphology.c:2392
unsigned short Quantum
Definition: magick-type.h:86
double xi
Definition: geometry.h:108
MagickExport KernelInfo * CloneKernelInfo(const KernelInfo *kernel)
Definition: morphology.c:2213
MagickExport char * DestroyString(char *string)
Definition: string.c:788
MagickExport void * AcquireMagickMemory(const size_t size)
Definition: memory.c:552
MagickExport MagickStatusType ParseGeometry(const char *geometry, GeometryInfo *geometry_info)
Definition: geometry.c:866
static void SetPixelChannel(const Image *magick_restrict image, const PixelChannel channel, const Quantum quantum, Quantum *magick_restrict pixel)
static double StringToDouble(const char *magick_restrict string, char *magick_restrict *sentinal)
ssize_t x
Definition: geometry.h:118
MagickExport void * RelinquishMagickMemory(void *memory)
Definition: memory.c:1162
CompositeOperator compose
Definition: image.h:234
MagickExport void UnityAddKernelInfo(KernelInfo *kernel, const double scale)
Definition: morphology.c:4739
CompositeOperator
Definition: composite.h:25
#define MagickPrivate
KernelInfoType
Definition: morphology.h:27
#define MagickExport
ssize_t y
Definition: morphology.h:112
MagickExport MagickBooleanType SyncCacheViewAuthenticPixels(CacheView *magick_restrict cache_view, ExceptionInfo *exception)
Definition: cache-view.c:1100
MagickExport CacheView * AcquireAuthenticCacheView(const Image *image, ExceptionInfo *exception)
Definition: cache-view.c:112
PixelTrait
Definition: pixel.h:137
MagickExport MagickRealType GetPixelIntensity(const Image *magick_restrict image, const Quantum *magick_restrict pixel)
Definition: pixel.c:2358
static void ExpandRotateKernelInfo(KernelInfo *, const double)
Definition: morphology.c:2420
#define MorphologyTag
#define KernelRank
MagickExport Image * DestroyImage(Image *image)
Definition: image.c:1179
MagickExport Image * CloneImage(const Image *image, const size_t columns, const size_t rows, const MagickBooleanType detach, ExceptionInfo *exception)
Definition: image.c:787
#define QuantumRange
Definition: magick-type.h:87
MagickExport MagickBooleanType SetImageProgress(const Image *image, const char *tag, const MagickOffsetType offset, const MagickSizeType extent)
Definition: monitor.c:136
MagickRealType * values
Definition: morphology.h:116