MagickCore 7.1.2-0
Convert, Edit, Or Compose Bitmap Images
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feature.c
1/*
2%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3% %
4% %
5% %
6% FFFFF EEEEE AAA TTTTT U U RRRR EEEEE %
7% F E A A T U U R R E %
8% FFF EEE AAAAA T U U RRRR EEE %
9% F E A A T U U R R E %
10% F EEEEE A A T UUU R R EEEEE %
11% %
12% %
13% MagickCore Image Feature Methods %
14% %
15% Software Design %
16% Cristy %
17% July 1992 %
18% %
19% %
20% Copyright @ 1999 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%
37%
38*/
39
40/*
41 Include declarations.
42*/
43#include "MagickCore/studio.h"
44#include "MagickCore/animate.h"
45#include "MagickCore/artifact.h"
46#include "MagickCore/blob.h"
47#include "MagickCore/blob-private.h"
48#include "MagickCore/cache.h"
49#include "MagickCore/cache-private.h"
50#include "MagickCore/cache-view.h"
51#include "MagickCore/channel.h"
52#include "MagickCore/client.h"
53#include "MagickCore/color.h"
54#include "MagickCore/color-private.h"
55#include "MagickCore/colorspace.h"
56#include "MagickCore/colorspace-private.h"
57#include "MagickCore/composite.h"
58#include "MagickCore/composite-private.h"
59#include "MagickCore/compress.h"
60#include "MagickCore/constitute.h"
61#include "MagickCore/display.h"
62#include "MagickCore/draw.h"
63#include "MagickCore/enhance.h"
64#include "MagickCore/exception.h"
65#include "MagickCore/exception-private.h"
66#include "MagickCore/feature.h"
67#include "MagickCore/gem.h"
68#include "MagickCore/geometry.h"
69#include "MagickCore/list.h"
70#include "MagickCore/image-private.h"
71#include "MagickCore/magic.h"
72#include "MagickCore/magick.h"
73#include "MagickCore/matrix.h"
74#include "MagickCore/memory_.h"
75#include "MagickCore/module.h"
76#include "MagickCore/monitor.h"
77#include "MagickCore/monitor-private.h"
78#include "MagickCore/morphology-private.h"
79#include "MagickCore/nt-base-private.h"
80#include "MagickCore/option.h"
81#include "MagickCore/paint.h"
82#include "MagickCore/pixel-accessor.h"
83#include "MagickCore/profile.h"
84#include "MagickCore/property.h"
85#include "MagickCore/quantize.h"
86#include "MagickCore/quantum-private.h"
87#include "MagickCore/random_.h"
88#include "MagickCore/resource_.h"
89#include "MagickCore/segment.h"
90#include "MagickCore/semaphore.h"
91#include "MagickCore/signature-private.h"
92#include "MagickCore/statistic-private.h"
93#include "MagickCore/string_.h"
94#include "MagickCore/thread-private.h"
95#include "MagickCore/timer.h"
96#include "MagickCore/utility.h"
97#include "MagickCore/utility-private.h"
98#include "MagickCore/version.h"
99
100/*
101%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
102% %
103% %
104% %
105% C a n n y E d g e I m a g e %
106% %
107% %
108% %
109%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
110%
111% CannyEdgeImage() uses a multi-stage algorithm to detect a wide range of
112% edges in images.
113%
114% The format of the CannyEdgeImage method is:
115%
116% Image *CannyEdgeImage(const Image *image,const double radius,
117% const double sigma,const double lower_percent,
118% const double upper_percent,ExceptionInfo *exception)
119%
120% A description of each parameter follows:
121%
122% o image: the image.
123%
124% o radius: the radius of the gaussian smoothing filter.
125%
126% o sigma: the sigma of the gaussian smoothing filter.
127%
128% o lower_percent: percentage of edge pixels in the lower threshold.
129%
130% o upper_percent: percentage of edge pixels in the upper threshold.
131%
132% o exception: return any errors or warnings in this structure.
133%
134*/
135
136typedef struct _CannyInfo
137{
138 double
139 magnitude,
140 intensity;
141
142 int
143 orientation;
144
145 ssize_t
146 x,
147 y;
148} CannyInfo;
149
150static inline MagickBooleanType IsAuthenticPixel(const Image *image,
151 const ssize_t x,const ssize_t y)
152{
153 if ((x < 0) || (x >= (ssize_t) image->columns))
154 return(MagickFalse);
155 if ((y < 0) || (y >= (ssize_t) image->rows))
156 return(MagickFalse);
157 return(MagickTrue);
158}
159
160static MagickBooleanType TraceEdges(Image *edge_image,CacheView *edge_view,
161 MatrixInfo *canny_cache,const ssize_t x,const ssize_t y,
162 const double lower_threshold,ExceptionInfo *exception)
163{
165 edge,
166 pixel;
167
168 MagickBooleanType
169 status;
170
171 Quantum
172 *q;
173
174 ssize_t
175 i;
176
177 q=GetCacheViewAuthenticPixels(edge_view,x,y,1,1,exception);
178 if (q == (Quantum *) NULL)
179 return(MagickFalse);
180 *q=QuantumRange;
181 status=SyncCacheViewAuthenticPixels(edge_view,exception);
182 if (status == MagickFalse)
183 return(MagickFalse);
184 if (GetMatrixElement(canny_cache,0,0,&edge) == MagickFalse)
185 return(MagickFalse);
186 edge.x=x;
187 edge.y=y;
188 if (SetMatrixElement(canny_cache,0,0,&edge) == MagickFalse)
189 return(MagickFalse);
190 for (i=1; i != 0; )
191 {
192 ssize_t
193 v;
194
195 i--;
196 status=GetMatrixElement(canny_cache,i,0,&edge);
197 if (status == MagickFalse)
198 return(MagickFalse);
199 for (v=(-1); v <= 1; v++)
200 {
201 ssize_t
202 u;
203
204 for (u=(-1); u <= 1; u++)
205 {
206 if ((u == 0) && (v == 0))
207 continue;
208 if (IsAuthenticPixel(edge_image,edge.x+u,edge.y+v) == MagickFalse)
209 continue;
210 /*
211 Not an edge if gradient value is below the lower threshold.
212 */
213 q=GetCacheViewAuthenticPixels(edge_view,edge.x+u,edge.y+v,1,1,
214 exception);
215 if (q == (Quantum *) NULL)
216 return(MagickFalse);
217 status=GetMatrixElement(canny_cache,edge.x+u,edge.y+v,&pixel);
218 if (status == MagickFalse)
219 return(MagickFalse);
220 if ((GetPixelIntensity(edge_image,q) == 0.0) &&
221 (pixel.intensity >= lower_threshold))
222 {
223 *q=QuantumRange;
224 status=SyncCacheViewAuthenticPixels(edge_view,exception);
225 if (status == MagickFalse)
226 return(MagickFalse);
227 edge.x+=u;
228 edge.y+=v;
229 status=SetMatrixElement(canny_cache,i,0,&edge);
230 if (status == MagickFalse)
231 return(MagickFalse);
232 i++;
233 }
234 }
235 }
236 }
237 return(MagickTrue);
238}
239
240MagickExport Image *CannyEdgeImage(const Image *image,const double radius,
241 const double sigma,const double lower_percent,const double upper_percent,
242 ExceptionInfo *exception)
243{
244#define CannyEdgeImageTag "CannyEdge/Image"
245
247 *edge_view;
248
250 element;
251
252 char
253 geometry[MagickPathExtent];
254
255 double
256 lower_threshold,
257 max,
258 min,
259 upper_threshold;
260
261 Image
262 *edge_image;
263
265 *kernel_info;
266
267 MagickBooleanType
268 status;
269
270 MagickOffsetType
271 progress;
272
274 *canny_cache;
275
276 ssize_t
277 y;
278
279 assert(image != (const Image *) NULL);
280 assert(image->signature == MagickCoreSignature);
281 assert(exception != (ExceptionInfo *) NULL);
282 assert(exception->signature == MagickCoreSignature);
283 if (IsEventLogging() != MagickFalse)
284 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
285 /*
286 Filter out noise.
287 */
288 (void) FormatLocaleString(geometry,MagickPathExtent,
289 "blur:%.20gx%.20g;blur:%.20gx%.20g+90",radius,sigma,radius,sigma);
290 kernel_info=AcquireKernelInfo(geometry,exception);
291 if (kernel_info == (KernelInfo *) NULL)
292 ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
293 edge_image=MorphologyImage(image,ConvolveMorphology,1,kernel_info,exception);
294 kernel_info=DestroyKernelInfo(kernel_info);
295 if (edge_image == (Image *) NULL)
296 return((Image *) NULL);
297 if (TransformImageColorspace(edge_image,GRAYColorspace,exception) == MagickFalse)
298 {
299 edge_image=DestroyImage(edge_image);
300 return((Image *) NULL);
301 }
302 (void) SetImageAlphaChannel(edge_image,OffAlphaChannel,exception);
303 /*
304 Find the intensity gradient of the image.
305 */
306 canny_cache=AcquireMatrixInfo(edge_image->columns,edge_image->rows,
307 sizeof(CannyInfo),exception);
308 if (canny_cache == (MatrixInfo *) NULL)
309 {
310 edge_image=DestroyImage(edge_image);
311 return((Image *) NULL);
312 }
313 status=MagickTrue;
314 edge_view=AcquireVirtualCacheView(edge_image,exception);
315#if defined(MAGICKCORE_OPENMP_SUPPORT)
316 #pragma omp parallel for schedule(static) shared(status) \
317 magick_number_threads(edge_image,edge_image,edge_image->rows,1)
318#endif
319 for (y=0; y < (ssize_t) edge_image->rows; y++)
320 {
321 const Quantum
322 *magick_restrict p;
323
324 ssize_t
325 x;
326
327 if (status == MagickFalse)
328 continue;
329 p=GetCacheViewVirtualPixels(edge_view,0,y,edge_image->columns+1,2,
330 exception);
331 if (p == (const Quantum *) NULL)
332 {
333 status=MagickFalse;
334 continue;
335 }
336 for (x=0; x < (ssize_t) edge_image->columns; x++)
337 {
339 pixel;
340
341 double
342 dx,
343 dy;
344
345 const Quantum
346 *magick_restrict kernel_pixels;
347
348 ssize_t
349 v;
350
351 static double
352 Gx[2][2] =
353 {
354 { -1.0, +1.0 },
355 { -1.0, +1.0 }
356 },
357 Gy[2][2] =
358 {
359 { +1.0, +1.0 },
360 { -1.0, -1.0 }
361 };
362
363 (void) memset(&pixel,0,sizeof(pixel));
364 dx=0.0;
365 dy=0.0;
366 kernel_pixels=p;
367 for (v=0; v < 2; v++)
368 {
369 ssize_t
370 u;
371
372 for (u=0; u < 2; u++)
373 {
374 double
375 intensity;
376
377 intensity=GetPixelIntensity(edge_image,kernel_pixels+u);
378 dx+=0.5*Gx[v][u]*intensity;
379 dy+=0.5*Gy[v][u]*intensity;
380 }
381 kernel_pixels+=edge_image->columns+1;
382 }
383 pixel.magnitude=hypot(dx,dy);
384 pixel.orientation=0;
385 if (fabs(dx) > MagickEpsilon)
386 {
387 double
388 slope;
389
390 slope=dy/dx;
391 if (slope < 0.0)
392 {
393 if (slope < -2.41421356237)
394 pixel.orientation=0;
395 else
396 if (slope < -0.414213562373)
397 pixel.orientation=1;
398 else
399 pixel.orientation=2;
400 }
401 else
402 {
403 if (slope > 2.41421356237)
404 pixel.orientation=0;
405 else
406 if (slope > 0.414213562373)
407 pixel.orientation=3;
408 else
409 pixel.orientation=2;
410 }
411 }
412 if (SetMatrixElement(canny_cache,x,y,&pixel) == MagickFalse)
413 continue;
414 p+=(ptrdiff_t) GetPixelChannels(edge_image);
415 }
416 }
417 edge_view=DestroyCacheView(edge_view);
418 /*
419 Non-maxima suppression, remove pixels that are not considered to be part
420 of an edge.
421 */
422 progress=0;
423 (void) GetMatrixElement(canny_cache,0,0,&element);
424 max=element.intensity;
425 min=element.intensity;
426 edge_view=AcquireAuthenticCacheView(edge_image,exception);
427#if defined(MAGICKCORE_OPENMP_SUPPORT)
428 #pragma omp parallel for schedule(static) shared(status) \
429 magick_number_threads(edge_image,edge_image,edge_image->rows,1)
430#endif
431 for (y=0; y < (ssize_t) edge_image->rows; y++)
432 {
433 Quantum
434 *magick_restrict q;
435
436 ssize_t
437 x;
438
439 if (status == MagickFalse)
440 continue;
441 q=GetCacheViewAuthenticPixels(edge_view,0,y,edge_image->columns,1,
442 exception);
443 if (q == (Quantum *) NULL)
444 {
445 status=MagickFalse;
446 continue;
447 }
448 for (x=0; x < (ssize_t) edge_image->columns; x++)
449 {
451 alpha_pixel,
452 beta_pixel,
453 pixel;
454
455 (void) GetMatrixElement(canny_cache,x,y,&pixel);
456 switch (pixel.orientation)
457 {
458 case 0:
459 default:
460 {
461 /*
462 0 degrees, north and south.
463 */
464 (void) GetMatrixElement(canny_cache,x,y-1,&alpha_pixel);
465 (void) GetMatrixElement(canny_cache,x,y+1,&beta_pixel);
466 break;
467 }
468 case 1:
469 {
470 /*
471 45 degrees, northwest and southeast.
472 */
473 (void) GetMatrixElement(canny_cache,x-1,y-1,&alpha_pixel);
474 (void) GetMatrixElement(canny_cache,x+1,y+1,&beta_pixel);
475 break;
476 }
477 case 2:
478 {
479 /*
480 90 degrees, east and west.
481 */
482 (void) GetMatrixElement(canny_cache,x-1,y,&alpha_pixel);
483 (void) GetMatrixElement(canny_cache,x+1,y,&beta_pixel);
484 break;
485 }
486 case 3:
487 {
488 /*
489 135 degrees, northeast and southwest.
490 */
491 (void) GetMatrixElement(canny_cache,x+1,y-1,&beta_pixel);
492 (void) GetMatrixElement(canny_cache,x-1,y+1,&alpha_pixel);
493 break;
494 }
495 }
496 pixel.intensity=pixel.magnitude;
497 if ((pixel.magnitude < alpha_pixel.magnitude) ||
498 (pixel.magnitude < beta_pixel.magnitude))
499 pixel.intensity=0;
500 (void) SetMatrixElement(canny_cache,x,y,&pixel);
501#if defined(MAGICKCORE_OPENMP_SUPPORT)
502 #pragma omp critical (MagickCore_CannyEdgeImage)
503#endif
504 {
505 if (pixel.intensity < min)
506 min=pixel.intensity;
507 if (pixel.intensity > max)
508 max=pixel.intensity;
509 }
510 *q=(Quantum) 0;
511 q+=(ptrdiff_t) GetPixelChannels(edge_image);
512 }
513 if (SyncCacheViewAuthenticPixels(edge_view,exception) == MagickFalse)
514 status=MagickFalse;
515 }
516 edge_view=DestroyCacheView(edge_view);
517 /*
518 Estimate hysteresis threshold.
519 */
520 lower_threshold=lower_percent*(max-min)+min;
521 upper_threshold=upper_percent*(max-min)+min;
522 /*
523 Hysteresis threshold.
524 */
525 edge_view=AcquireAuthenticCacheView(edge_image,exception);
526 for (y=0; y < (ssize_t) edge_image->rows; y++)
527 {
528 ssize_t
529 x;
530
531 if (status == MagickFalse)
532 continue;
533 for (x=0; x < (ssize_t) edge_image->columns; x++)
534 {
536 pixel;
537
538 const Quantum
539 *magick_restrict p;
540
541 /*
542 Edge if pixel gradient higher than upper threshold.
543 */
544 p=GetCacheViewVirtualPixels(edge_view,x,y,1,1,exception);
545 if (p == (const Quantum *) NULL)
546 continue;
547 status=GetMatrixElement(canny_cache,x,y,&pixel);
548 if (status == MagickFalse)
549 continue;
550 if ((GetPixelIntensity(edge_image,p) == 0.0) &&
551 (pixel.intensity >= upper_threshold))
552 status=TraceEdges(edge_image,edge_view,canny_cache,x,y,lower_threshold,
553 exception);
554 }
555 if (image->progress_monitor != (MagickProgressMonitor) NULL)
556 {
557 MagickBooleanType
558 proceed;
559
560#if defined(MAGICKCORE_OPENMP_SUPPORT)
561 #pragma omp atomic
562#endif
563 progress++;
564 proceed=SetImageProgress(image,CannyEdgeImageTag,progress,image->rows);
565 if (proceed == MagickFalse)
566 status=MagickFalse;
567 }
568 }
569 edge_view=DestroyCacheView(edge_view);
570 /*
571 Free resources.
572 */
573 canny_cache=DestroyMatrixInfo(canny_cache);
574 return(edge_image);
575}
576
577/*
578%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
579% %
580% %
581% %
582% G e t I m a g e F e a t u r e s %
583% %
584% %
585% %
586%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
587%
588% GetImageFeatures() returns features for each channel in the image in
589% each of four directions (horizontal, vertical, left and right diagonals)
590% for the specified distance. The features include the angular second
591% moment, contrast, correlation, sum of squares: variance, inverse difference
592% moment, sum average, sum variance, sum entropy, entropy, difference variance,
593% difference entropy, information measures of correlation 1, information
594% measures of correlation 2, and maximum correlation coefficient. You can
595% access the red channel contrast, for example, like this:
596%
597% channel_features=GetImageFeatures(image,1,exception);
598% contrast=channel_features[RedPixelChannel].contrast[0];
599%
600% Use MagickRelinquishMemory() to free the features buffer.
601%
602% The format of the GetImageFeatures method is:
603%
604% ChannelFeatures *GetImageFeatures(const Image *image,
605% const size_t distance,ExceptionInfo *exception)
606%
607% A description of each parameter follows:
608%
609% o image: the image.
610%
611% o distance: the distance.
612%
613% o exception: return any errors or warnings in this structure.
614%
615*/
616MagickExport ChannelFeatures *GetImageFeatures(const Image *image,
617 const size_t distance,ExceptionInfo *exception)
618{
619 typedef struct _ChannelStatistics
620 {
622 direction[4]; /* horizontal, vertical, left and right diagonals */
624
626 *image_view;
627
629 *channel_features;
630
632 **cooccurrence,
633 correlation,
634 *density_x,
635 *density_xy,
636 *density_y,
637 entropy_x,
638 entropy_xy,
639 entropy_xy1,
640 entropy_xy2,
641 entropy_y,
642 mean,
643 **Q,
644 *sum,
645 sum_squares,
646 variance;
647
649 gray,
650 *grays;
651
652 MagickBooleanType
653 status;
654
655 ssize_t
656 i,
657 r;
658
659 size_t
660 length;
661
662 unsigned int
663 number_grays;
664
665 assert(image != (Image *) NULL);
666 assert(image->signature == MagickCoreSignature);
667 if (IsEventLogging() != MagickFalse)
668 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
669 if ((image->columns < (distance+1)) || (image->rows < (distance+1)))
670 return((ChannelFeatures *) NULL);
671 length=MaxPixelChannels+1UL;
672 channel_features=(ChannelFeatures *) AcquireQuantumMemory(length,
673 sizeof(*channel_features));
674 if (channel_features == (ChannelFeatures *) NULL)
675 ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
676 (void) memset(channel_features,0,length*
677 sizeof(*channel_features));
678 /*
679 Form grays.
680 */
681 grays=(PixelPacket *) AcquireQuantumMemory(MaxMap+1UL,sizeof(*grays));
682 if (grays == (PixelPacket *) NULL)
683 {
684 channel_features=(ChannelFeatures *) RelinquishMagickMemory(
685 channel_features);
686 (void) ThrowMagickException(exception,GetMagickModule(),
687 ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
688 return(channel_features);
689 }
690 for (i=0; i <= (ssize_t) MaxMap; i++)
691 {
692 grays[i].red=(~0U);
693 grays[i].green=(~0U);
694 grays[i].blue=(~0U);
695 grays[i].alpha=(~0U);
696 grays[i].black=(~0U);
697 }
698 status=MagickTrue;
699 image_view=AcquireVirtualCacheView(image,exception);
700#if defined(MAGICKCORE_OPENMP_SUPPORT)
701 #pragma omp parallel for schedule(static) shared(status) \
702 magick_number_threads(image,image,image->rows,1)
703#endif
704 for (r=0; r < (ssize_t) image->rows; r++)
705 {
706 const Quantum
707 *magick_restrict p;
708
709 ssize_t
710 x;
711
712 if (status == MagickFalse)
713 continue;
714 p=GetCacheViewVirtualPixels(image_view,0,r,image->columns,1,exception);
715 if (p == (const Quantum *) NULL)
716 {
717 status=MagickFalse;
718 continue;
719 }
720 for (x=0; x < (ssize_t) image->columns; x++)
721 {
722 grays[ScaleQuantumToMap(GetPixelRed(image,p))].red=
723 ScaleQuantumToMap(GetPixelRed(image,p));
724 grays[ScaleQuantumToMap(GetPixelGreen(image,p))].green=
725 ScaleQuantumToMap(GetPixelGreen(image,p));
726 grays[ScaleQuantumToMap(GetPixelBlue(image,p))].blue=
727 ScaleQuantumToMap(GetPixelBlue(image,p));
728 if (image->colorspace == CMYKColorspace)
729 grays[ScaleQuantumToMap(GetPixelBlack(image,p))].black=
730 ScaleQuantumToMap(GetPixelBlack(image,p));
731 if (image->alpha_trait != UndefinedPixelTrait)
732 grays[ScaleQuantumToMap(GetPixelAlpha(image,p))].alpha=
733 ScaleQuantumToMap(GetPixelAlpha(image,p));
734 p+=(ptrdiff_t) GetPixelChannels(image);
735 }
736 }
737 image_view=DestroyCacheView(image_view);
738 if (status == MagickFalse)
739 {
740 grays=(PixelPacket *) RelinquishMagickMemory(grays);
741 channel_features=(ChannelFeatures *) RelinquishMagickMemory(
742 channel_features);
743 return(channel_features);
744 }
745 (void) memset(&gray,0,sizeof(gray));
746 for (i=0; i <= (ssize_t) MaxMap; i++)
747 {
748 if (grays[i].red != ~0U)
749 grays[gray.red++].red=grays[i].red;
750 if (grays[i].green != ~0U)
751 grays[gray.green++].green=grays[i].green;
752 if (grays[i].blue != ~0U)
753 grays[gray.blue++].blue=grays[i].blue;
754 if (image->colorspace == CMYKColorspace)
755 if (grays[i].black != ~0U)
756 grays[gray.black++].black=grays[i].black;
757 if (image->alpha_trait != UndefinedPixelTrait)
758 if (grays[i].alpha != ~0U)
759 grays[gray.alpha++].alpha=grays[i].alpha;
760 }
761 /*
762 Allocate spatial dependence matrix.
763 */
764 number_grays=gray.red;
765 if (gray.green > number_grays)
766 number_grays=gray.green;
767 if (gray.blue > number_grays)
768 number_grays=gray.blue;
769 if (image->colorspace == CMYKColorspace)
770 if (gray.black > number_grays)
771 number_grays=gray.black;
772 if (image->alpha_trait != UndefinedPixelTrait)
773 if (gray.alpha > number_grays)
774 number_grays=gray.alpha;
775 cooccurrence=(ChannelStatistics **) AcquireQuantumMemory(number_grays,
776 sizeof(*cooccurrence));
777 density_x=(ChannelStatistics *) AcquireQuantumMemory(number_grays+1,
778 2*sizeof(*density_x));
779 density_xy=(ChannelStatistics *) AcquireQuantumMemory(number_grays+1,
780 2*sizeof(*density_xy));
781 density_y=(ChannelStatistics *) AcquireQuantumMemory(number_grays+1,
782 2*sizeof(*density_y));
783 Q=(ChannelStatistics **) AcquireQuantumMemory(number_grays,sizeof(*Q));
784 sum=(ChannelStatistics *) AcquireQuantumMemory(number_grays,sizeof(*sum));
785 if ((cooccurrence == (ChannelStatistics **) NULL) ||
786 (density_x == (ChannelStatistics *) NULL) ||
787 (density_xy == (ChannelStatistics *) NULL) ||
788 (density_y == (ChannelStatistics *) NULL) ||
789 (Q == (ChannelStatistics **) NULL) ||
790 (sum == (ChannelStatistics *) NULL))
791 {
792 if (Q != (ChannelStatistics **) NULL)
793 {
794 for (i=0; i < (ssize_t) number_grays; i++)
795 Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]);
796 Q=(ChannelStatistics **) RelinquishMagickMemory(Q);
797 }
798 if (sum != (ChannelStatistics *) NULL)
799 sum=(ChannelStatistics *) RelinquishMagickMemory(sum);
800 if (density_y != (ChannelStatistics *) NULL)
801 density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y);
802 if (density_xy != (ChannelStatistics *) NULL)
803 density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy);
804 if (density_x != (ChannelStatistics *) NULL)
805 density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x);
806 if (cooccurrence != (ChannelStatistics **) NULL)
807 {
808 for (i=0; i < (ssize_t) number_grays; i++)
809 cooccurrence[i]=(ChannelStatistics *)
810 RelinquishMagickMemory(cooccurrence[i]);
811 cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(
812 cooccurrence);
813 }
814 grays=(PixelPacket *) RelinquishMagickMemory(grays);
815 channel_features=(ChannelFeatures *) RelinquishMagickMemory(
816 channel_features);
817 (void) ThrowMagickException(exception,GetMagickModule(),
818 ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
819 return(channel_features);
820 }
821 (void) memset(&correlation,0,sizeof(correlation));
822 (void) memset(density_x,0,2*(number_grays+1)*sizeof(*density_x));
823 (void) memset(density_xy,0,2*(number_grays+1)*sizeof(*density_xy));
824 (void) memset(density_y,0,2*(number_grays+1)*sizeof(*density_y));
825 (void) memset(&mean,0,sizeof(mean));
826 (void) memset(sum,0,number_grays*sizeof(*sum));
827 (void) memset(&sum_squares,0,sizeof(sum_squares));
828 (void) memset(density_xy,0,2*number_grays*sizeof(*density_xy));
829 (void) memset(&entropy_x,0,sizeof(entropy_x));
830 (void) memset(&entropy_xy,0,sizeof(entropy_xy));
831 (void) memset(&entropy_xy1,0,sizeof(entropy_xy1));
832 (void) memset(&entropy_xy2,0,sizeof(entropy_xy2));
833 (void) memset(&entropy_y,0,sizeof(entropy_y));
834 (void) memset(&variance,0,sizeof(variance));
835 for (i=0; i < (ssize_t) number_grays; i++)
836 {
837 cooccurrence[i]=(ChannelStatistics *) AcquireQuantumMemory(number_grays,
838 sizeof(**cooccurrence));
839 Q[i]=(ChannelStatistics *) AcquireQuantumMemory(number_grays,sizeof(**Q));
840 if ((cooccurrence[i] == (ChannelStatistics *) NULL) ||
841 (Q[i] == (ChannelStatistics *) NULL))
842 break;
843 (void) memset(cooccurrence[i],0,number_grays*
844 sizeof(**cooccurrence));
845 (void) memset(Q[i],0,number_grays*sizeof(**Q));
846 }
847 if (i < (ssize_t) number_grays)
848 {
849 for (i--; i >= 0; i--)
850 {
851 if (Q[i] != (ChannelStatistics *) NULL)
852 Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]);
853 if (cooccurrence[i] != (ChannelStatistics *) NULL)
854 cooccurrence[i]=(ChannelStatistics *)
855 RelinquishMagickMemory(cooccurrence[i]);
856 }
857 Q=(ChannelStatistics **) RelinquishMagickMemory(Q);
858 cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence);
859 sum=(ChannelStatistics *) RelinquishMagickMemory(sum);
860 density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y);
861 density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy);
862 density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x);
863 grays=(PixelPacket *) RelinquishMagickMemory(grays);
864 channel_features=(ChannelFeatures *) RelinquishMagickMemory(
865 channel_features);
866 (void) ThrowMagickException(exception,GetMagickModule(),
867 ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
868 return(channel_features);
869 }
870 /*
871 Initialize spatial dependence matrix.
872 */
873 status=MagickTrue;
874 image_view=AcquireVirtualCacheView(image,exception);
875 for (r=0; r < (ssize_t) image->rows; r++)
876 {
877 const Quantum
878 *magick_restrict p;
879
880 ssize_t
881 x;
882
883 ssize_t
884 offset,
885 u,
886 v;
887
888 if (status == MagickFalse)
889 continue;
890 p=GetCacheViewVirtualPixels(image_view,-(ssize_t) distance,r,image->columns+
891 2*distance,distance+2,exception);
892 if (p == (const Quantum *) NULL)
893 {
894 status=MagickFalse;
895 continue;
896 }
897 p+=(ptrdiff_t) distance*GetPixelChannels(image);;
898 for (x=0; x < (ssize_t) image->columns; x++)
899 {
900 for (i=0; i < 4; i++)
901 {
902 switch (i)
903 {
904 case 0:
905 default:
906 {
907 /*
908 Horizontal adjacency.
909 */
910 offset=(ssize_t) distance;
911 break;
912 }
913 case 1:
914 {
915 /*
916 Vertical adjacency.
917 */
918 offset=(ssize_t) (image->columns+2*distance);
919 break;
920 }
921 case 2:
922 {
923 /*
924 Right diagonal adjacency.
925 */
926 offset=(ssize_t) ((image->columns+2*distance)-distance);
927 break;
928 }
929 case 3:
930 {
931 /*
932 Left diagonal adjacency.
933 */
934 offset=(ssize_t) ((image->columns+2*distance)+distance);
935 break;
936 }
937 }
938 u=0;
939 v=0;
940 while (grays[u].red != ScaleQuantumToMap(GetPixelRed(image,p)))
941 u++;
942 while (grays[v].red != ScaleQuantumToMap(GetPixelRed(image,p+offset*(ssize_t) GetPixelChannels(image))))
943 v++;
944 cooccurrence[u][v].direction[i].red++;
945 cooccurrence[v][u].direction[i].red++;
946 u=0;
947 v=0;
948 while (grays[u].green != ScaleQuantumToMap(GetPixelGreen(image,p)))
949 u++;
950 while (grays[v].green != ScaleQuantumToMap(GetPixelGreen(image,p+offset*(ssize_t) GetPixelChannels(image))))
951 v++;
952 cooccurrence[u][v].direction[i].green++;
953 cooccurrence[v][u].direction[i].green++;
954 u=0;
955 v=0;
956 while (grays[u].blue != ScaleQuantumToMap(GetPixelBlue(image,p)))
957 u++;
958 while (grays[v].blue != ScaleQuantumToMap(GetPixelBlue(image,p+offset*(ssize_t) GetPixelChannels(image))))
959 v++;
960 cooccurrence[u][v].direction[i].blue++;
961 cooccurrence[v][u].direction[i].blue++;
962 if (image->colorspace == CMYKColorspace)
963 {
964 u=0;
965 v=0;
966 while (grays[u].black != ScaleQuantumToMap(GetPixelBlack(image,p)))
967 u++;
968 while (grays[v].black != ScaleQuantumToMap(GetPixelBlack(image,p+offset*(ssize_t) GetPixelChannels(image))))
969 v++;
970 cooccurrence[u][v].direction[i].black++;
971 cooccurrence[v][u].direction[i].black++;
972 }
973 if (image->alpha_trait != UndefinedPixelTrait)
974 {
975 u=0;
976 v=0;
977 while (grays[u].alpha != ScaleQuantumToMap(GetPixelAlpha(image,p)))
978 u++;
979 while (grays[v].alpha != ScaleQuantumToMap(GetPixelAlpha(image,p+offset*(ssize_t) GetPixelChannels(image))))
980 v++;
981 cooccurrence[u][v].direction[i].alpha++;
982 cooccurrence[v][u].direction[i].alpha++;
983 }
984 }
985 p+=(ptrdiff_t) GetPixelChannels(image);
986 }
987 }
988 grays=(PixelPacket *) RelinquishMagickMemory(grays);
989 image_view=DestroyCacheView(image_view);
990 if (status == MagickFalse)
991 {
992 for (i=0; i < (ssize_t) number_grays; i++)
993 cooccurrence[i]=(ChannelStatistics *)
994 RelinquishMagickMemory(cooccurrence[i]);
995 cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence);
996 channel_features=(ChannelFeatures *) RelinquishMagickMemory(
997 channel_features);
998 (void) ThrowMagickException(exception,GetMagickModule(),
999 ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
1000 return(channel_features);
1001 }
1002 /*
1003 Normalize spatial dependence matrix.
1004 */
1005 for (i=0; i < 4; i++)
1006 {
1007 double
1008 normalize;
1009
1010 ssize_t
1011 y;
1012
1013 switch (i)
1014 {
1015 case 0:
1016 default:
1017 {
1018 /*
1019 Horizontal adjacency.
1020 */
1021 normalize=2.0*image->rows*(image->columns-distance);
1022 break;
1023 }
1024 case 1:
1025 {
1026 /*
1027 Vertical adjacency.
1028 */
1029 normalize=2.0*(image->rows-distance)*image->columns;
1030 break;
1031 }
1032 case 2:
1033 {
1034 /*
1035 Right diagonal adjacency.
1036 */
1037 normalize=2.0*(image->rows-distance)*(image->columns-distance);
1038 break;
1039 }
1040 case 3:
1041 {
1042 /*
1043 Left diagonal adjacency.
1044 */
1045 normalize=2.0*(image->rows-distance)*(image->columns-distance);
1046 break;
1047 }
1048 }
1049 normalize=MagickSafeReciprocal(normalize);
1050 for (y=0; y < (ssize_t) number_grays; y++)
1051 {
1052 ssize_t
1053 x;
1054
1055 for (x=0; x < (ssize_t) number_grays; x++)
1056 {
1057 cooccurrence[x][y].direction[i].red*=normalize;
1058 cooccurrence[x][y].direction[i].green*=normalize;
1059 cooccurrence[x][y].direction[i].blue*=normalize;
1060 if (image->colorspace == CMYKColorspace)
1061 cooccurrence[x][y].direction[i].black*=normalize;
1062 if (image->alpha_trait != UndefinedPixelTrait)
1063 cooccurrence[x][y].direction[i].alpha*=normalize;
1064 }
1065 }
1066 }
1067 /*
1068 Compute texture features.
1069 */
1070#if defined(MAGICKCORE_OPENMP_SUPPORT)
1071 #pragma omp parallel for schedule(static) shared(status) \
1072 magick_number_threads(image,image,number_grays,1)
1073#endif
1074 for (i=0; i < 4; i++)
1075 {
1076 ssize_t
1077 y;
1078
1079 for (y=0; y < (ssize_t) number_grays; y++)
1080 {
1081 ssize_t
1082 x;
1083
1084 for (x=0; x < (ssize_t) number_grays; x++)
1085 {
1086 /*
1087 Angular second moment: measure of homogeneity of the image.
1088 */
1089 channel_features[RedPixelChannel].angular_second_moment[i]+=
1090 cooccurrence[x][y].direction[i].red*
1091 cooccurrence[x][y].direction[i].red;
1092 channel_features[GreenPixelChannel].angular_second_moment[i]+=
1093 cooccurrence[x][y].direction[i].green*
1094 cooccurrence[x][y].direction[i].green;
1095 channel_features[BluePixelChannel].angular_second_moment[i]+=
1096 cooccurrence[x][y].direction[i].blue*
1097 cooccurrence[x][y].direction[i].blue;
1098 if (image->colorspace == CMYKColorspace)
1099 channel_features[BlackPixelChannel].angular_second_moment[i]+=
1100 cooccurrence[x][y].direction[i].black*
1101 cooccurrence[x][y].direction[i].black;
1102 if (image->alpha_trait != UndefinedPixelTrait)
1103 channel_features[AlphaPixelChannel].angular_second_moment[i]+=
1104 cooccurrence[x][y].direction[i].alpha*
1105 cooccurrence[x][y].direction[i].alpha;
1106 /*
1107 Correlation: measure of linear-dependencies in the image.
1108 */
1109 sum[y].direction[i].red+=cooccurrence[x][y].direction[i].red;
1110 sum[y].direction[i].green+=cooccurrence[x][y].direction[i].green;
1111 sum[y].direction[i].blue+=cooccurrence[x][y].direction[i].blue;
1112 if (image->colorspace == CMYKColorspace)
1113 sum[y].direction[i].black+=cooccurrence[x][y].direction[i].black;
1114 if (image->alpha_trait != UndefinedPixelTrait)
1115 sum[y].direction[i].alpha+=cooccurrence[x][y].direction[i].alpha;
1116 correlation.direction[i].red+=x*y*cooccurrence[x][y].direction[i].red;
1117 correlation.direction[i].green+=x*y*
1118 cooccurrence[x][y].direction[i].green;
1119 correlation.direction[i].blue+=x*y*
1120 cooccurrence[x][y].direction[i].blue;
1121 if (image->colorspace == CMYKColorspace)
1122 correlation.direction[i].black+=x*y*
1123 cooccurrence[x][y].direction[i].black;
1124 if (image->alpha_trait != UndefinedPixelTrait)
1125 correlation.direction[i].alpha+=x*y*
1126 cooccurrence[x][y].direction[i].alpha;
1127 /*
1128 Inverse Difference Moment.
1129 */
1130 channel_features[RedPixelChannel].inverse_difference_moment[i]+=
1131 cooccurrence[x][y].direction[i].red/((y-x)*(y-x)+1);
1132 channel_features[GreenPixelChannel].inverse_difference_moment[i]+=
1133 cooccurrence[x][y].direction[i].green/((y-x)*(y-x)+1);
1134 channel_features[BluePixelChannel].inverse_difference_moment[i]+=
1135 cooccurrence[x][y].direction[i].blue/((y-x)*(y-x)+1);
1136 if (image->colorspace == CMYKColorspace)
1137 channel_features[BlackPixelChannel].inverse_difference_moment[i]+=
1138 cooccurrence[x][y].direction[i].black/((y-x)*(y-x)+1);
1139 if (image->alpha_trait != UndefinedPixelTrait)
1140 channel_features[AlphaPixelChannel].inverse_difference_moment[i]+=
1141 cooccurrence[x][y].direction[i].alpha/((y-x)*(y-x)+1);
1142 /*
1143 Sum average.
1144 */
1145 density_xy[y+x+2].direction[i].red+=
1146 cooccurrence[x][y].direction[i].red;
1147 density_xy[y+x+2].direction[i].green+=
1148 cooccurrence[x][y].direction[i].green;
1149 density_xy[y+x+2].direction[i].blue+=
1150 cooccurrence[x][y].direction[i].blue;
1151 if (image->colorspace == CMYKColorspace)
1152 density_xy[y+x+2].direction[i].black+=
1153 cooccurrence[x][y].direction[i].black;
1154 if (image->alpha_trait != UndefinedPixelTrait)
1155 density_xy[y+x+2].direction[i].alpha+=
1156 cooccurrence[x][y].direction[i].alpha;
1157 /*
1158 Entropy.
1159 */
1160 channel_features[RedPixelChannel].entropy[i]-=
1161 cooccurrence[x][y].direction[i].red*
1162 log2(cooccurrence[x][y].direction[i].red);
1163 channel_features[GreenPixelChannel].entropy[i]-=
1164 cooccurrence[x][y].direction[i].green*
1165 log2(cooccurrence[x][y].direction[i].green);
1166 channel_features[BluePixelChannel].entropy[i]-=
1167 cooccurrence[x][y].direction[i].blue*
1168 log2(cooccurrence[x][y].direction[i].blue);
1169 if (image->colorspace == CMYKColorspace)
1170 channel_features[BlackPixelChannel].entropy[i]-=
1171 cooccurrence[x][y].direction[i].black*
1172 log2(cooccurrence[x][y].direction[i].black);
1173 if (image->alpha_trait != UndefinedPixelTrait)
1174 channel_features[AlphaPixelChannel].entropy[i]-=
1175 cooccurrence[x][y].direction[i].alpha*
1176 log2(cooccurrence[x][y].direction[i].alpha);
1177 /*
1178 Information Measures of Correlation.
1179 */
1180 density_x[x].direction[i].red+=cooccurrence[x][y].direction[i].red;
1181 density_x[x].direction[i].green+=cooccurrence[x][y].direction[i].green;
1182 density_x[x].direction[i].blue+=cooccurrence[x][y].direction[i].blue;
1183 if (image->alpha_trait != UndefinedPixelTrait)
1184 density_x[x].direction[i].alpha+=
1185 cooccurrence[x][y].direction[i].alpha;
1186 if (image->colorspace == CMYKColorspace)
1187 density_x[x].direction[i].black+=
1188 cooccurrence[x][y].direction[i].black;
1189 density_y[y].direction[i].red+=cooccurrence[x][y].direction[i].red;
1190 density_y[y].direction[i].green+=cooccurrence[x][y].direction[i].green;
1191 density_y[y].direction[i].blue+=cooccurrence[x][y].direction[i].blue;
1192 if (image->colorspace == CMYKColorspace)
1193 density_y[y].direction[i].black+=
1194 cooccurrence[x][y].direction[i].black;
1195 if (image->alpha_trait != UndefinedPixelTrait)
1196 density_y[y].direction[i].alpha+=
1197 cooccurrence[x][y].direction[i].alpha;
1198 }
1199 mean.direction[i].red+=y*sum[y].direction[i].red;
1200 sum_squares.direction[i].red+=y*y*sum[y].direction[i].red;
1201 mean.direction[i].green+=y*sum[y].direction[i].green;
1202 sum_squares.direction[i].green+=y*y*sum[y].direction[i].green;
1203 mean.direction[i].blue+=y*sum[y].direction[i].blue;
1204 sum_squares.direction[i].blue+=y*y*sum[y].direction[i].blue;
1205 if (image->colorspace == CMYKColorspace)
1206 {
1207 mean.direction[i].black+=y*sum[y].direction[i].black;
1208 sum_squares.direction[i].black+=y*y*sum[y].direction[i].black;
1209 }
1210 if (image->alpha_trait != UndefinedPixelTrait)
1211 {
1212 mean.direction[i].alpha+=y*sum[y].direction[i].alpha;
1213 sum_squares.direction[i].alpha+=y*y*sum[y].direction[i].alpha;
1214 }
1215 }
1216 /*
1217 Correlation: measure of linear-dependencies in the image.
1218 */
1219 channel_features[RedPixelChannel].correlation[i]=
1220 (correlation.direction[i].red-mean.direction[i].red*
1221 mean.direction[i].red)/(sqrt(sum_squares.direction[i].red-
1222 (mean.direction[i].red*mean.direction[i].red))*sqrt(
1223 sum_squares.direction[i].red-(mean.direction[i].red*
1224 mean.direction[i].red)));
1225 channel_features[GreenPixelChannel].correlation[i]=
1226 (correlation.direction[i].green-mean.direction[i].green*
1227 mean.direction[i].green)/(sqrt(sum_squares.direction[i].green-
1228 (mean.direction[i].green*mean.direction[i].green))*sqrt(
1229 sum_squares.direction[i].green-(mean.direction[i].green*
1230 mean.direction[i].green)));
1231 channel_features[BluePixelChannel].correlation[i]=
1232 (correlation.direction[i].blue-mean.direction[i].blue*
1233 mean.direction[i].blue)/(sqrt(sum_squares.direction[i].blue-
1234 (mean.direction[i].blue*mean.direction[i].blue))*sqrt(
1235 sum_squares.direction[i].blue-(mean.direction[i].blue*
1236 mean.direction[i].blue)));
1237 if (image->colorspace == CMYKColorspace)
1238 channel_features[BlackPixelChannel].correlation[i]=
1239 (correlation.direction[i].black-mean.direction[i].black*
1240 mean.direction[i].black)/(sqrt(sum_squares.direction[i].black-
1241 (mean.direction[i].black*mean.direction[i].black))*sqrt(
1242 sum_squares.direction[i].black-(mean.direction[i].black*
1243 mean.direction[i].black)));
1244 if (image->alpha_trait != UndefinedPixelTrait)
1245 channel_features[AlphaPixelChannel].correlation[i]=
1246 (correlation.direction[i].alpha-mean.direction[i].alpha*
1247 mean.direction[i].alpha)/(sqrt(sum_squares.direction[i].alpha-
1248 (mean.direction[i].alpha*mean.direction[i].alpha))*sqrt(
1249 sum_squares.direction[i].alpha-(mean.direction[i].alpha*
1250 mean.direction[i].alpha)));
1251 }
1252 /*
1253 Compute more texture features.
1254 */
1255#if defined(MAGICKCORE_OPENMP_SUPPORT)
1256 #pragma omp parallel for schedule(static) shared(status) \
1257 magick_number_threads(image,image,number_grays,1)
1258#endif
1259 for (i=0; i < 4; i++)
1260 {
1261 ssize_t
1262 x;
1263
1264 for (x=2; x < (ssize_t) (2*number_grays); x++)
1265 {
1266 /*
1267 Sum average.
1268 */
1269 channel_features[RedPixelChannel].sum_average[i]+=
1270 x*density_xy[x].direction[i].red;
1271 channel_features[GreenPixelChannel].sum_average[i]+=
1272 x*density_xy[x].direction[i].green;
1273 channel_features[BluePixelChannel].sum_average[i]+=
1274 x*density_xy[x].direction[i].blue;
1275 if (image->colorspace == CMYKColorspace)
1276 channel_features[BlackPixelChannel].sum_average[i]+=
1277 x*density_xy[x].direction[i].black;
1278 if (image->alpha_trait != UndefinedPixelTrait)
1279 channel_features[AlphaPixelChannel].sum_average[i]+=
1280 x*density_xy[x].direction[i].alpha;
1281 /*
1282 Sum entropy.
1283 */
1284 channel_features[RedPixelChannel].sum_entropy[i]-=
1285 density_xy[x].direction[i].red*
1286 log2(density_xy[x].direction[i].red);
1287 channel_features[GreenPixelChannel].sum_entropy[i]-=
1288 density_xy[x].direction[i].green*
1289 log2(density_xy[x].direction[i].green);
1290 channel_features[BluePixelChannel].sum_entropy[i]-=
1291 density_xy[x].direction[i].blue*
1292 log2(density_xy[x].direction[i].blue);
1293 if (image->colorspace == CMYKColorspace)
1294 channel_features[BlackPixelChannel].sum_entropy[i]-=
1295 density_xy[x].direction[i].black*
1296 log2(density_xy[x].direction[i].black);
1297 if (image->alpha_trait != UndefinedPixelTrait)
1298 channel_features[AlphaPixelChannel].sum_entropy[i]-=
1299 density_xy[x].direction[i].alpha*
1300 log2(density_xy[x].direction[i].alpha);
1301 /*
1302 Sum variance.
1303 */
1304 channel_features[RedPixelChannel].sum_variance[i]+=
1305 (x-channel_features[RedPixelChannel].sum_entropy[i])*
1306 (x-channel_features[RedPixelChannel].sum_entropy[i])*
1307 density_xy[x].direction[i].red;
1308 channel_features[GreenPixelChannel].sum_variance[i]+=
1309 (x-channel_features[GreenPixelChannel].sum_entropy[i])*
1310 (x-channel_features[GreenPixelChannel].sum_entropy[i])*
1311 density_xy[x].direction[i].green;
1312 channel_features[BluePixelChannel].sum_variance[i]+=
1313 (x-channel_features[BluePixelChannel].sum_entropy[i])*
1314 (x-channel_features[BluePixelChannel].sum_entropy[i])*
1315 density_xy[x].direction[i].blue;
1316 if (image->colorspace == CMYKColorspace)
1317 channel_features[BlackPixelChannel].sum_variance[i]+=
1318 (x-channel_features[BlackPixelChannel].sum_entropy[i])*
1319 (x-channel_features[BlackPixelChannel].sum_entropy[i])*
1320 density_xy[x].direction[i].black;
1321 if (image->alpha_trait != UndefinedPixelTrait)
1322 channel_features[AlphaPixelChannel].sum_variance[i]+=
1323 (x-channel_features[AlphaPixelChannel].sum_entropy[i])*
1324 (x-channel_features[AlphaPixelChannel].sum_entropy[i])*
1325 density_xy[x].direction[i].alpha;
1326 }
1327 }
1328 /*
1329 Compute more texture features.
1330 */
1331#if defined(MAGICKCORE_OPENMP_SUPPORT)
1332 #pragma omp parallel for schedule(static) shared(status) \
1333 magick_number_threads(image,image,number_grays,1)
1334#endif
1335 for (i=0; i < 4; i++)
1336 {
1337 ssize_t
1338 y;
1339
1340 for (y=0; y < (ssize_t) number_grays; y++)
1341 {
1342 ssize_t
1343 x;
1344
1345 for (x=0; x < (ssize_t) number_grays; x++)
1346 {
1347 /*
1348 Sum of Squares: Variance
1349 */
1350 variance.direction[i].red+=(y-mean.direction[i].red+1)*
1351 (y-mean.direction[i].red+1)*cooccurrence[x][y].direction[i].red;
1352 variance.direction[i].green+=(y-mean.direction[i].green+1)*
1353 (y-mean.direction[i].green+1)*cooccurrence[x][y].direction[i].green;
1354 variance.direction[i].blue+=(y-mean.direction[i].blue+1)*
1355 (y-mean.direction[i].blue+1)*cooccurrence[x][y].direction[i].blue;
1356 if (image->colorspace == CMYKColorspace)
1357 variance.direction[i].black+=(y-mean.direction[i].black+1)*
1358 (y-mean.direction[i].black+1)*cooccurrence[x][y].direction[i].black;
1359 if (image->alpha_trait != UndefinedPixelTrait)
1360 variance.direction[i].alpha+=(y-mean.direction[i].alpha+1)*
1361 (y-mean.direction[i].alpha+1)*
1362 cooccurrence[x][y].direction[i].alpha;
1363 /*
1364 Sum average / Difference Variance.
1365 */
1366 density_xy[MagickAbsoluteValue(y-x)].direction[i].red+=
1367 cooccurrence[x][y].direction[i].red;
1368 density_xy[MagickAbsoluteValue(y-x)].direction[i].green+=
1369 cooccurrence[x][y].direction[i].green;
1370 density_xy[MagickAbsoluteValue(y-x)].direction[i].blue+=
1371 cooccurrence[x][y].direction[i].blue;
1372 if (image->colorspace == CMYKColorspace)
1373 density_xy[MagickAbsoluteValue(y-x)].direction[i].black+=
1374 cooccurrence[x][y].direction[i].black;
1375 if (image->alpha_trait != UndefinedPixelTrait)
1376 density_xy[MagickAbsoluteValue(y-x)].direction[i].alpha+=
1377 cooccurrence[x][y].direction[i].alpha;
1378 /*
1379 Information Measures of Correlation.
1380 */
1381 entropy_xy.direction[i].red-=cooccurrence[x][y].direction[i].red*
1382 log2(cooccurrence[x][y].direction[i].red);
1383 entropy_xy.direction[i].green-=cooccurrence[x][y].direction[i].green*
1384 log2(cooccurrence[x][y].direction[i].green);
1385 entropy_xy.direction[i].blue-=cooccurrence[x][y].direction[i].blue*
1386 log2(cooccurrence[x][y].direction[i].blue);
1387 if (image->colorspace == CMYKColorspace)
1388 entropy_xy.direction[i].black-=cooccurrence[x][y].direction[i].black*
1389 log2(cooccurrence[x][y].direction[i].black);
1390 if (image->alpha_trait != UndefinedPixelTrait)
1391 entropy_xy.direction[i].alpha-=
1392 cooccurrence[x][y].direction[i].alpha*log2(
1393 cooccurrence[x][y].direction[i].alpha);
1394 entropy_xy1.direction[i].red-=(cooccurrence[x][y].direction[i].red*
1395 log2(density_x[x].direction[i].red*density_y[y].direction[i].red));
1396 entropy_xy1.direction[i].green-=(cooccurrence[x][y].direction[i].green*
1397 log2(density_x[x].direction[i].green*
1398 density_y[y].direction[i].green));
1399 entropy_xy1.direction[i].blue-=(cooccurrence[x][y].direction[i].blue*
1400 log2(density_x[x].direction[i].blue*density_y[y].direction[i].blue));
1401 if (image->colorspace == CMYKColorspace)
1402 entropy_xy1.direction[i].black-=(
1403 cooccurrence[x][y].direction[i].black*log2(
1404 density_x[x].direction[i].black*density_y[y].direction[i].black));
1405 if (image->alpha_trait != UndefinedPixelTrait)
1406 entropy_xy1.direction[i].alpha-=(
1407 cooccurrence[x][y].direction[i].alpha*log2(
1408 density_x[x].direction[i].alpha*density_y[y].direction[i].alpha));
1409 entropy_xy2.direction[i].red-=(density_x[x].direction[i].red*
1410 density_y[y].direction[i].red*log2(density_x[x].direction[i].red*
1411 density_y[y].direction[i].red));
1412 entropy_xy2.direction[i].green-=(density_x[x].direction[i].green*
1413 density_y[y].direction[i].green*log2(density_x[x].direction[i].green*
1414 density_y[y].direction[i].green));
1415 entropy_xy2.direction[i].blue-=(density_x[x].direction[i].blue*
1416 density_y[y].direction[i].blue*log2(density_x[x].direction[i].blue*
1417 density_y[y].direction[i].blue));
1418 if (image->colorspace == CMYKColorspace)
1419 entropy_xy2.direction[i].black-=(density_x[x].direction[i].black*
1420 density_y[y].direction[i].black*log2(
1421 density_x[x].direction[i].black*density_y[y].direction[i].black));
1422 if (image->alpha_trait != UndefinedPixelTrait)
1423 entropy_xy2.direction[i].alpha-=(density_x[x].direction[i].alpha*
1424 density_y[y].direction[i].alpha*log2(
1425 density_x[x].direction[i].alpha*density_y[y].direction[i].alpha));
1426 }
1427 }
1428 channel_features[RedPixelChannel].variance_sum_of_squares[i]=
1429 variance.direction[i].red;
1430 channel_features[GreenPixelChannel].variance_sum_of_squares[i]=
1431 variance.direction[i].green;
1432 channel_features[BluePixelChannel].variance_sum_of_squares[i]=
1433 variance.direction[i].blue;
1434 if (image->colorspace == CMYKColorspace)
1435 channel_features[BlackPixelChannel].variance_sum_of_squares[i]=
1436 variance.direction[i].black;
1437 if (image->alpha_trait != UndefinedPixelTrait)
1438 channel_features[AlphaPixelChannel].variance_sum_of_squares[i]=
1439 variance.direction[i].alpha;
1440 }
1441 /*
1442 Compute more texture features.
1443 */
1444 (void) memset(&variance,0,sizeof(variance));
1445 (void) memset(&sum_squares,0,sizeof(sum_squares));
1446#if defined(MAGICKCORE_OPENMP_SUPPORT)
1447 #pragma omp parallel for schedule(static) shared(status) \
1448 magick_number_threads(image,image,number_grays,1)
1449#endif
1450 for (i=0; i < 4; i++)
1451 {
1452 ssize_t
1453 x;
1454
1455 for (x=0; x < (ssize_t) number_grays; x++)
1456 {
1457 /*
1458 Difference variance.
1459 */
1460 variance.direction[i].red+=density_xy[x].direction[i].red;
1461 variance.direction[i].green+=density_xy[x].direction[i].green;
1462 variance.direction[i].blue+=density_xy[x].direction[i].blue;
1463 if (image->colorspace == CMYKColorspace)
1464 variance.direction[i].black+=density_xy[x].direction[i].black;
1465 if (image->alpha_trait != UndefinedPixelTrait)
1466 variance.direction[i].alpha+=density_xy[x].direction[i].alpha;
1467 sum_squares.direction[i].red+=density_xy[x].direction[i].red*
1468 density_xy[x].direction[i].red;
1469 sum_squares.direction[i].green+=density_xy[x].direction[i].green*
1470 density_xy[x].direction[i].green;
1471 sum_squares.direction[i].blue+=density_xy[x].direction[i].blue*
1472 density_xy[x].direction[i].blue;
1473 if (image->colorspace == CMYKColorspace)
1474 sum_squares.direction[i].black+=density_xy[x].direction[i].black*
1475 density_xy[x].direction[i].black;
1476 if (image->alpha_trait != UndefinedPixelTrait)
1477 sum_squares.direction[i].alpha+=density_xy[x].direction[i].alpha*
1478 density_xy[x].direction[i].alpha;
1479 /*
1480 Difference entropy.
1481 */
1482 channel_features[RedPixelChannel].difference_entropy[i]-=
1483 density_xy[x].direction[i].red*
1484 log2(density_xy[x].direction[i].red);
1485 channel_features[GreenPixelChannel].difference_entropy[i]-=
1486 density_xy[x].direction[i].green*
1487 log2(density_xy[x].direction[i].green);
1488 channel_features[BluePixelChannel].difference_entropy[i]-=
1489 density_xy[x].direction[i].blue*
1490 log2(density_xy[x].direction[i].blue);
1491 if (image->colorspace == CMYKColorspace)
1492 channel_features[BlackPixelChannel].difference_entropy[i]-=
1493 density_xy[x].direction[i].black*
1494 log2(density_xy[x].direction[i].black);
1495 if (image->alpha_trait != UndefinedPixelTrait)
1496 channel_features[AlphaPixelChannel].difference_entropy[i]-=
1497 density_xy[x].direction[i].alpha*
1498 log2(density_xy[x].direction[i].alpha);
1499 /*
1500 Information Measures of Correlation.
1501 */
1502 entropy_x.direction[i].red-=(density_x[x].direction[i].red*
1503 log2(density_x[x].direction[i].red));
1504 entropy_x.direction[i].green-=(density_x[x].direction[i].green*
1505 log2(density_x[x].direction[i].green));
1506 entropy_x.direction[i].blue-=(density_x[x].direction[i].blue*
1507 log2(density_x[x].direction[i].blue));
1508 if (image->colorspace == CMYKColorspace)
1509 entropy_x.direction[i].black-=(density_x[x].direction[i].black*
1510 log2(density_x[x].direction[i].black));
1511 if (image->alpha_trait != UndefinedPixelTrait)
1512 entropy_x.direction[i].alpha-=(density_x[x].direction[i].alpha*
1513 log2(density_x[x].direction[i].alpha));
1514 entropy_y.direction[i].red-=(density_y[x].direction[i].red*
1515 log2(density_y[x].direction[i].red));
1516 entropy_y.direction[i].green-=(density_y[x].direction[i].green*
1517 log2(density_y[x].direction[i].green));
1518 entropy_y.direction[i].blue-=(density_y[x].direction[i].blue*
1519 log2(density_y[x].direction[i].blue));
1520 if (image->colorspace == CMYKColorspace)
1521 entropy_y.direction[i].black-=(density_y[x].direction[i].black*
1522 log2(density_y[x].direction[i].black));
1523 if (image->alpha_trait != UndefinedPixelTrait)
1524 entropy_y.direction[i].alpha-=(density_y[x].direction[i].alpha*
1525 log2(density_y[x].direction[i].alpha));
1526 }
1527 /*
1528 Difference variance.
1529 */
1530 channel_features[RedPixelChannel].difference_variance[i]=
1531 (((double) number_grays*number_grays*sum_squares.direction[i].red)-
1532 (variance.direction[i].red*variance.direction[i].red))/
1533 ((double) number_grays*number_grays*number_grays*number_grays);
1534 channel_features[GreenPixelChannel].difference_variance[i]=
1535 (((double) number_grays*number_grays*sum_squares.direction[i].green)-
1536 (variance.direction[i].green*variance.direction[i].green))/
1537 ((double) number_grays*number_grays*number_grays*number_grays);
1538 channel_features[BluePixelChannel].difference_variance[i]=
1539 (((double) number_grays*number_grays*sum_squares.direction[i].blue)-
1540 (variance.direction[i].blue*variance.direction[i].blue))/
1541 ((double) number_grays*number_grays*number_grays*number_grays);
1542 if (image->colorspace == CMYKColorspace)
1543 channel_features[BlackPixelChannel].difference_variance[i]=
1544 (((double) number_grays*number_grays*sum_squares.direction[i].black)-
1545 (variance.direction[i].black*variance.direction[i].black))/
1546 ((double) number_grays*number_grays*number_grays*number_grays);
1547 if (image->alpha_trait != UndefinedPixelTrait)
1548 channel_features[AlphaPixelChannel].difference_variance[i]=
1549 (((double) number_grays*number_grays*sum_squares.direction[i].alpha)-
1550 (variance.direction[i].alpha*variance.direction[i].alpha))/
1551 ((double) number_grays*number_grays*number_grays*number_grays);
1552 /*
1553 Information Measures of Correlation.
1554 */
1555 channel_features[RedPixelChannel].measure_of_correlation_1[i]=
1556 (entropy_xy.direction[i].red-entropy_xy1.direction[i].red)/
1557 (entropy_x.direction[i].red > entropy_y.direction[i].red ?
1558 entropy_x.direction[i].red : entropy_y.direction[i].red);
1559 channel_features[GreenPixelChannel].measure_of_correlation_1[i]=
1560 (entropy_xy.direction[i].green-entropy_xy1.direction[i].green)/
1561 (entropy_x.direction[i].green > entropy_y.direction[i].green ?
1562 entropy_x.direction[i].green : entropy_y.direction[i].green);
1563 channel_features[BluePixelChannel].measure_of_correlation_1[i]=
1564 (entropy_xy.direction[i].blue-entropy_xy1.direction[i].blue)/
1565 (entropy_x.direction[i].blue > entropy_y.direction[i].blue ?
1566 entropy_x.direction[i].blue : entropy_y.direction[i].blue);
1567 if (image->colorspace == CMYKColorspace)
1568 channel_features[BlackPixelChannel].measure_of_correlation_1[i]=
1569 (entropy_xy.direction[i].black-entropy_xy1.direction[i].black)/
1570 (entropy_x.direction[i].black > entropy_y.direction[i].black ?
1571 entropy_x.direction[i].black : entropy_y.direction[i].black);
1572 if (image->alpha_trait != UndefinedPixelTrait)
1573 channel_features[AlphaPixelChannel].measure_of_correlation_1[i]=
1574 (entropy_xy.direction[i].alpha-entropy_xy1.direction[i].alpha)/
1575 (entropy_x.direction[i].alpha > entropy_y.direction[i].alpha ?
1576 entropy_x.direction[i].alpha : entropy_y.direction[i].alpha);
1577 channel_features[RedPixelChannel].measure_of_correlation_2[i]=
1578 (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].red-
1579 entropy_xy.direction[i].red)))));
1580 channel_features[GreenPixelChannel].measure_of_correlation_2[i]=
1581 (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].green-
1582 entropy_xy.direction[i].green)))));
1583 channel_features[BluePixelChannel].measure_of_correlation_2[i]=
1584 (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].blue-
1585 entropy_xy.direction[i].blue)))));
1586 if (image->colorspace == CMYKColorspace)
1587 channel_features[BlackPixelChannel].measure_of_correlation_2[i]=
1588 (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].black-
1589 entropy_xy.direction[i].black)))));
1590 if (image->alpha_trait != UndefinedPixelTrait)
1591 channel_features[AlphaPixelChannel].measure_of_correlation_2[i]=
1592 (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].alpha-
1593 entropy_xy.direction[i].alpha)))));
1594 }
1595 /*
1596 Compute more texture features.
1597 */
1598#if defined(MAGICKCORE_OPENMP_SUPPORT)
1599 #pragma omp parallel for schedule(static) shared(status) \
1600 magick_number_threads(image,image,number_grays,1)
1601#endif
1602 for (i=0; i < 4; i++)
1603 {
1604 ssize_t
1605 z;
1606
1607 for (z=0; z < (ssize_t) number_grays; z++)
1608 {
1609 ssize_t
1610 y;
1611
1613 pixel;
1614
1615 (void) memset(&pixel,0,sizeof(pixel));
1616 for (y=0; y < (ssize_t) number_grays; y++)
1617 {
1618 ssize_t
1619 x;
1620
1621 for (x=0; x < (ssize_t) number_grays; x++)
1622 {
1623 /*
1624 Contrast: amount of local variations present in an image.
1625 */
1626 if (((y-x) == z) || ((x-y) == z))
1627 {
1628 pixel.direction[i].red+=cooccurrence[x][y].direction[i].red;
1629 pixel.direction[i].green+=cooccurrence[x][y].direction[i].green;
1630 pixel.direction[i].blue+=cooccurrence[x][y].direction[i].blue;
1631 if (image->colorspace == CMYKColorspace)
1632 pixel.direction[i].black+=cooccurrence[x][y].direction[i].black;
1633 if (image->alpha_trait != UndefinedPixelTrait)
1634 pixel.direction[i].alpha+=
1635 cooccurrence[x][y].direction[i].alpha;
1636 }
1637 /*
1638 Maximum Correlation Coefficient.
1639 */
1640 if ((fabs(density_x[z].direction[i].red) > MagickEpsilon) &&
1641 (fabs(density_y[x].direction[i].red) > MagickEpsilon))
1642 Q[z][y].direction[i].red+=cooccurrence[z][x].direction[i].red*
1643 cooccurrence[y][x].direction[i].red/density_x[z].direction[i].red/
1644 density_y[x].direction[i].red;
1645 if ((fabs(density_x[z].direction[i].green) > MagickEpsilon) &&
1646 (fabs(density_y[x].direction[i].red) > MagickEpsilon))
1647 Q[z][y].direction[i].green+=cooccurrence[z][x].direction[i].green*
1648 cooccurrence[y][x].direction[i].green/
1649 density_x[z].direction[i].green/density_y[x].direction[i].red;
1650 if ((fabs(density_x[z].direction[i].blue) > MagickEpsilon) &&
1651 (fabs(density_y[x].direction[i].blue) > MagickEpsilon))
1652 Q[z][y].direction[i].blue+=cooccurrence[z][x].direction[i].blue*
1653 cooccurrence[y][x].direction[i].blue/
1654 density_x[z].direction[i].blue/density_y[x].direction[i].blue;
1655 if (image->colorspace == CMYKColorspace)
1656 if ((fabs(density_x[z].direction[i].black) > MagickEpsilon) &&
1657 (fabs(density_y[x].direction[i].black) > MagickEpsilon))
1658 Q[z][y].direction[i].black+=cooccurrence[z][x].direction[i].black*
1659 cooccurrence[y][x].direction[i].black/
1660 density_x[z].direction[i].black/density_y[x].direction[i].black;
1661 if (image->alpha_trait != UndefinedPixelTrait)
1662 if ((fabs(density_x[z].direction[i].alpha) > MagickEpsilon) &&
1663 (fabs(density_y[x].direction[i].alpha) > MagickEpsilon))
1664 Q[z][y].direction[i].alpha+=
1665 cooccurrence[z][x].direction[i].alpha*
1666 cooccurrence[y][x].direction[i].alpha/
1667 density_x[z].direction[i].alpha/
1668 density_y[x].direction[i].alpha;
1669 }
1670 }
1671 channel_features[RedPixelChannel].contrast[i]+=z*z*
1672 pixel.direction[i].red;
1673 channel_features[GreenPixelChannel].contrast[i]+=z*z*
1674 pixel.direction[i].green;
1675 channel_features[BluePixelChannel].contrast[i]+=z*z*
1676 pixel.direction[i].blue;
1677 if (image->colorspace == CMYKColorspace)
1678 channel_features[BlackPixelChannel].contrast[i]+=z*z*
1679 pixel.direction[i].black;
1680 if (image->alpha_trait != UndefinedPixelTrait)
1681 channel_features[AlphaPixelChannel].contrast[i]+=z*z*
1682 pixel.direction[i].alpha;
1683 }
1684 /*
1685 Maximum Correlation Coefficient.
1686 Future: return second largest eigenvalue of Q.
1687 */
1688 channel_features[RedPixelChannel].maximum_correlation_coefficient[i]=
1689 sqrt(-1.0);
1690 channel_features[GreenPixelChannel].maximum_correlation_coefficient[i]=
1691 sqrt(-1.0);
1692 channel_features[BluePixelChannel].maximum_correlation_coefficient[i]=
1693 sqrt(-1.0);
1694 if (image->colorspace == CMYKColorspace)
1695 channel_features[BlackPixelChannel].maximum_correlation_coefficient[i]=
1696 sqrt(-1.0);
1697 if (image->alpha_trait != UndefinedPixelTrait)
1698 channel_features[AlphaPixelChannel].maximum_correlation_coefficient[i]=
1699 sqrt(-1.0);
1700 }
1701 /*
1702 Relinquish resources.
1703 */
1704 sum=(ChannelStatistics *) RelinquishMagickMemory(sum);
1705 for (i=0; i < (ssize_t) number_grays; i++)
1706 Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]);
1707 Q=(ChannelStatistics **) RelinquishMagickMemory(Q);
1708 density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y);
1709 density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy);
1710 density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x);
1711 for (i=0; i < (ssize_t) number_grays; i++)
1712 cooccurrence[i]=(ChannelStatistics *)
1713 RelinquishMagickMemory(cooccurrence[i]);
1714 cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence);
1715 return(channel_features);
1716}
1717
1718/*
1719%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1720% %
1721% %
1722% %
1723% H o u g h L i n e I m a g e %
1724% %
1725% %
1726% %
1727%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1728%
1729% HoughLineImage() can be used in conjunction with any binary edge extracted
1730% image (we recommend Canny) to identify lines in the image. The algorithm
1731% accumulates counts for every white pixel for every possible orientation (for
1732% angles from 0 to 179 in 1 degree increments) and distance from the center of
1733% the image to the corner (in 1 px increments) and stores the counts in an
1734% accumulator matrix of angle vs distance. The size of the accumulator is
1735% 180x(diagonal/2). Next it searches this space for peaks in counts and
1736% converts the locations of the peaks to slope and intercept in the normal
1737% x,y input image space. Use the slope/intercepts to find the endpoints
1738% clipped to the bounds of the image. The lines are then drawn. The counts
1739% are a measure of the length of the lines.
1740%
1741% The format of the HoughLineImage method is:
1742%
1743% Image *HoughLineImage(const Image *image,const size_t width,
1744% const size_t height,const size_t threshold,ExceptionInfo *exception)
1745%
1746% A description of each parameter follows:
1747%
1748% o image: the image.
1749%
1750% o width, height: find line pairs as local maxima in this neighborhood.
1751%
1752% o threshold: the line count threshold.
1753%
1754% o exception: return any errors or warnings in this structure.
1755%
1756*/
1757
1758static inline double MagickRound(double x)
1759{
1760 /*
1761 Round the fraction to nearest integer.
1762 */
1763 if ((x-floor(x)) < (ceil(x)-x))
1764 return(floor(x));
1765 return(ceil(x));
1766}
1767
1768static Image *RenderHoughLines(const ImageInfo *image_info,const size_t columns,
1769 const size_t rows,ExceptionInfo *exception)
1770{
1771#define BoundingBox "viewbox"
1772
1773 DrawInfo
1774 *draw_info;
1775
1776 Image
1777 *image;
1778
1779 MagickBooleanType
1780 status;
1781
1782 /*
1783 Open image.
1784 */
1785 image=AcquireImage(image_info,exception);
1786 status=OpenBlob(image_info,image,ReadBinaryBlobMode,exception);
1787 if (status == MagickFalse)
1788 {
1789 image=DestroyImageList(image);
1790 return((Image *) NULL);
1791 }
1792 image->columns=columns;
1793 image->rows=rows;
1794 draw_info=CloneDrawInfo(image_info,(DrawInfo *) NULL);
1795 draw_info->affine.sx=image->resolution.x == 0.0 ? 1.0 : image->resolution.x/
1796 DefaultResolution;
1797 draw_info->affine.sy=image->resolution.y == 0.0 ? 1.0 : image->resolution.y/
1798 DefaultResolution;
1799 image->columns=CastDoubleToSizeT(draw_info->affine.sx*image->columns);
1800 image->rows=CastDoubleToSizeT(draw_info->affine.sy*image->rows);
1801 status=SetImageExtent(image,image->columns,image->rows,exception);
1802 if (status == MagickFalse)
1803 return(DestroyImageList(image));
1804 if (SetImageBackgroundColor(image,exception) == MagickFalse)
1805 {
1806 image=DestroyImageList(image);
1807 return((Image *) NULL);
1808 }
1809 /*
1810 Render drawing.
1811 */
1812 if (GetBlobStreamData(image) == (unsigned char *) NULL)
1813 draw_info->primitive=FileToString(image->filename,~0UL,exception);
1814 else
1815 {
1816 draw_info->primitive=(char *) AcquireQuantumMemory(1,(size_t)
1817 GetBlobSize(image)+1);
1818 if (draw_info->primitive != (char *) NULL)
1819 {
1820 (void) memcpy(draw_info->primitive,GetBlobStreamData(image),
1821 (size_t) GetBlobSize(image));
1822 draw_info->primitive[GetBlobSize(image)]='\0';
1823 }
1824 }
1825 (void) DrawImage(image,draw_info,exception);
1826 draw_info=DestroyDrawInfo(draw_info);
1827 if (CloseBlob(image) == MagickFalse)
1828 image=DestroyImageList(image);
1829 return(GetFirstImageInList(image));
1830}
1831
1832MagickExport Image *HoughLineImage(const Image *image,const size_t width,
1833 const size_t height,const size_t threshold,ExceptionInfo *exception)
1834{
1835#define HoughLineImageTag "HoughLine/Image"
1836
1837 CacheView
1838 *image_view;
1839
1840 char
1841 message[MagickPathExtent],
1842 path[MagickPathExtent];
1843
1844 const char
1845 *artifact;
1846
1847 double
1848 hough_height;
1849
1850 Image
1851 *lines_image = NULL;
1852
1853 ImageInfo
1854 *image_info;
1855
1856 int
1857 file;
1858
1859 MagickBooleanType
1860 status;
1861
1862 MagickOffsetType
1863 progress;
1864
1866 *accumulator;
1867
1868 PointInfo
1869 center;
1870
1871 ssize_t
1872 y;
1873
1874 size_t
1875 accumulator_height,
1876 accumulator_width,
1877 line_count;
1878
1879 /*
1880 Create the accumulator.
1881 */
1882 assert(image != (const Image *) NULL);
1883 assert(image->signature == MagickCoreSignature);
1884 assert(exception != (ExceptionInfo *) NULL);
1885 assert(exception->signature == MagickCoreSignature);
1886 if (IsEventLogging() != MagickFalse)
1887 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
1888 accumulator_width=180;
1889 hough_height=((sqrt(2.0)*(double) (image->rows > image->columns ?
1890 image->rows : image->columns))/2.0);
1891 accumulator_height=(size_t) (2.0*hough_height);
1892 accumulator=AcquireMatrixInfo(accumulator_width,accumulator_height,
1893 sizeof(double),exception);
1894 if (accumulator == (MatrixInfo *) NULL)
1895 ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
1896 if (NullMatrix(accumulator) == MagickFalse)
1897 {
1898 accumulator=DestroyMatrixInfo(accumulator);
1899 ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
1900 }
1901 /*
1902 Populate the accumulator.
1903 */
1904 status=MagickTrue;
1905 progress=0;
1906 center.x=(double) image->columns/2.0;
1907 center.y=(double) image->rows/2.0;
1908 image_view=AcquireVirtualCacheView(image,exception);
1909 for (y=0; y < (ssize_t) image->rows; y++)
1910 {
1911 const Quantum
1912 *magick_restrict p;
1913
1914 ssize_t
1915 x;
1916
1917 if (status == MagickFalse)
1918 continue;
1919 p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
1920 if (p == (Quantum *) NULL)
1921 {
1922 status=MagickFalse;
1923 continue;
1924 }
1925 for (x=0; x < (ssize_t) image->columns; x++)
1926 {
1927 if (GetPixelIntensity(image,p) > ((double) QuantumRange/2.0))
1928 {
1929 ssize_t
1930 i;
1931
1932 for (i=0; i < 180; i++)
1933 {
1934 double
1935 count,
1936 radius;
1937
1938 radius=(((double) x-center.x)*cos(DegreesToRadians((double) i)))+
1939 (((double) y-center.y)*sin(DegreesToRadians((double) i)));
1940 (void) GetMatrixElement(accumulator,i,(ssize_t)
1941 MagickRound(radius+hough_height),&count);
1942 count++;
1943 (void) SetMatrixElement(accumulator,i,(ssize_t)
1944 MagickRound(radius+hough_height),&count);
1945 }
1946 }
1947 p+=(ptrdiff_t) GetPixelChannels(image);
1948 }
1949 if (image->progress_monitor != (MagickProgressMonitor) NULL)
1950 {
1951 MagickBooleanType
1952 proceed;
1953
1954#if defined(MAGICKCORE_OPENMP_SUPPORT)
1955 #pragma omp atomic
1956#endif
1957 progress++;
1958 proceed=SetImageProgress(image,CannyEdgeImageTag,progress,image->rows);
1959 if (proceed == MagickFalse)
1960 status=MagickFalse;
1961 }
1962 }
1963 image_view=DestroyCacheView(image_view);
1964 if (status == MagickFalse)
1965 {
1966 accumulator=DestroyMatrixInfo(accumulator);
1967 return((Image *) NULL);
1968 }
1969 /*
1970 Generate line segments from accumulator.
1971 */
1972 file=AcquireUniqueFileResource(path);
1973 if (file == -1)
1974 {
1975 accumulator=DestroyMatrixInfo(accumulator);
1976 return((Image *) NULL);
1977 }
1978 (void) FormatLocaleString(message,MagickPathExtent,
1979 "# Hough line transform: %.20gx%.20g%+.20g\n",(double) width,
1980 (double) height,(double) threshold);
1981 if (write(file,message,strlen(message)) != (ssize_t) strlen(message))
1982 status=MagickFalse;
1983 (void) FormatLocaleString(message,MagickPathExtent,
1984 "viewbox 0 0 %.20g %.20g\n",(double) image->columns,(double) image->rows);
1985 if (write(file,message,strlen(message)) != (ssize_t) strlen(message))
1986 status=MagickFalse;
1987 (void) FormatLocaleString(message,MagickPathExtent,
1988 "# x1,y1 x2,y2 # count angle distance\n");
1989 if (write(file,message,strlen(message)) != (ssize_t) strlen(message))
1990 status=MagickFalse;
1991 line_count=image->columns > image->rows ? image->columns/4 : image->rows/4;
1992 if (threshold != 0)
1993 line_count=threshold;
1994 for (y=0; y < (ssize_t) accumulator_height; y++)
1995 {
1996 ssize_t
1997 x;
1998
1999 for (x=0; x < (ssize_t) accumulator_width; x++)
2000 {
2001 double
2002 count;
2003
2004 (void) GetMatrixElement(accumulator,x,y,&count);
2005 if (count >= (double) line_count)
2006 {
2007 double
2008 maxima;
2009
2011 line;
2012
2013 ssize_t
2014 v;
2015
2016 /*
2017 Is point a local maxima?
2018 */
2019 maxima=count;
2020 for (v=(-((ssize_t) height/2)); v <= (((ssize_t) height/2)); v++)
2021 {
2022 ssize_t
2023 u;
2024
2025 for (u=(-((ssize_t) width/2)); u <= (((ssize_t) width/2)); u++)
2026 {
2027 if ((u != 0) || (v !=0))
2028 {
2029 (void) GetMatrixElement(accumulator,x+u,y+v,&count);
2030 if (count > maxima)
2031 {
2032 maxima=count;
2033 break;
2034 }
2035 }
2036 }
2037 if (u < (ssize_t) (width/2))
2038 break;
2039 }
2040 (void) GetMatrixElement(accumulator,x,y,&count);
2041 if (maxima > count)
2042 continue;
2043 if ((x >= 45) && (x <= 135))
2044 {
2045 /*
2046 y = (r-x cos(t))/sin(t)
2047 */
2048 line.x1=0.0;
2049 line.y1=((double) (y-(accumulator_height/2.0))-((line.x1-
2050 (image->columns/2.0))*cos(DegreesToRadians((double) x))))/
2051 sin(DegreesToRadians((double) x))+(image->rows/2.0);
2052 line.x2=(double) image->columns;
2053 line.y2=((double) (y-(accumulator_height/2.0))-((line.x2-
2054 (image->columns/2.0))*cos(DegreesToRadians((double) x))))/
2055 sin(DegreesToRadians((double) x))+(image->rows/2.0);
2056 }
2057 else
2058 {
2059 /*
2060 x = (r-y cos(t))/sin(t)
2061 */
2062 line.y1=0.0;
2063 line.x1=((double) (y-(accumulator_height/2.0))-((line.y1-
2064 (image->rows/2.0))*sin(DegreesToRadians((double) x))))/
2065 cos(DegreesToRadians((double) x))+(image->columns/2.0);
2066 line.y2=(double) image->rows;
2067 line.x2=((double) (y-(accumulator_height/2.0))-((line.y2-
2068 (image->rows/2.0))*sin(DegreesToRadians((double) x))))/
2069 cos(DegreesToRadians((double) x))+(image->columns/2.0);
2070 }
2071 (void) FormatLocaleString(message,MagickPathExtent,
2072 "line %g,%g %g,%g # %g %g %g\n",line.x1,line.y1,line.x2,line.y2,
2073 maxima,(double) x,(double) y);
2074 if (write(file,message,strlen(message)) != (ssize_t) strlen(message))
2075 status=MagickFalse;
2076 }
2077 }
2078 }
2079 (void) close_utf8(file);
2080 /*
2081 Render lines to image canvas.
2082 */
2083 image_info=AcquireImageInfo();
2084 image_info->background_color=image->background_color;
2085 (void) FormatLocaleString(image_info->filename,MagickPathExtent,"%s",path);
2086 artifact=GetImageArtifact(image,"background");
2087 if (artifact != (const char *) NULL)
2088 (void) SetImageOption(image_info,"background",artifact);
2089 artifact=GetImageArtifact(image,"fill");
2090 if (artifact != (const char *) NULL)
2091 (void) SetImageOption(image_info,"fill",artifact);
2092 artifact=GetImageArtifact(image,"stroke");
2093 if (artifact != (const char *) NULL)
2094 (void) SetImageOption(image_info,"stroke",artifact);
2095 artifact=GetImageArtifact(image,"strokewidth");
2096 if (artifact != (const char *) NULL)
2097 (void) SetImageOption(image_info,"strokewidth",artifact);
2098 lines_image=RenderHoughLines(image_info,image->columns,image->rows,exception);
2099 artifact=GetImageArtifact(image,"hough-lines:accumulator");
2100 if ((lines_image != (Image *) NULL) &&
2101 (IsStringTrue(artifact) != MagickFalse))
2102 {
2103 Image
2104 *accumulator_image;
2105
2106 accumulator_image=MatrixToImage(accumulator,exception);
2107 if (accumulator_image != (Image *) NULL)
2108 AppendImageToList(&lines_image,accumulator_image);
2109 }
2110 /*
2111 Free resources.
2112 */
2113 accumulator=DestroyMatrixInfo(accumulator);
2114 image_info=DestroyImageInfo(image_info);
2115 (void) RelinquishUniqueFileResource(path);
2116 return(GetFirstImageInList(lines_image));
2117}
2118
2119/*
2120%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2121% %
2122% %
2123% %
2124% M e a n S h i f t I m a g e %
2125% %
2126% %
2127% %
2128%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2129%
2130% MeanShiftImage() delineate arbitrarily shaped clusters in the image. For
2131% each pixel, it visits all the pixels in the neighborhood specified by
2132% the window centered at the pixel and excludes those that are outside the
2133% radius=(window-1)/2 surrounding the pixel. From those pixels, it finds those
2134% that are within the specified color distance from the current mean, and
2135% computes a new x,y centroid from those coordinates and a new mean. This new
2136% x,y centroid is used as the center for a new window. This process iterates
2137% until it converges and the final mean is replaces the (original window
2138% center) pixel value. It repeats this process for the next pixel, etc.,
2139% until it processes all pixels in the image. Results are typically better with
2140% colorspaces other than sRGB. We recommend YIQ, YUV or YCbCr.
2141%
2142% The format of the MeanShiftImage method is:
2143%
2144% Image *MeanShiftImage(const Image *image,const size_t width,
2145% const size_t height,const double color_distance,
2146% ExceptionInfo *exception)
2147%
2148% A description of each parameter follows:
2149%
2150% o image: the image.
2151%
2152% o width, height: find pixels in this neighborhood.
2153%
2154% o color_distance: the color distance.
2155%
2156% o exception: return any errors or warnings in this structure.
2157%
2158*/
2159MagickExport Image *MeanShiftImage(const Image *image,const size_t width,
2160 const size_t height,const double color_distance,ExceptionInfo *exception)
2161{
2162#define MaxMeanShiftIterations 100
2163#define MeanShiftImageTag "MeanShift/Image"
2164
2165 CacheView
2166 *image_view,
2167 *mean_view,
2168 *pixel_view;
2169
2170 Image
2171 *mean_image;
2172
2173 MagickBooleanType
2174 status;
2175
2176 MagickOffsetType
2177 progress;
2178
2179 ssize_t
2180 y;
2181
2182 assert(image != (const Image *) NULL);
2183 assert(image->signature == MagickCoreSignature);
2184 assert(exception != (ExceptionInfo *) NULL);
2185 assert(exception->signature == MagickCoreSignature);
2186 if (IsEventLogging() != MagickFalse)
2187 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
2188 mean_image=CloneImage(image,0,0,MagickTrue,exception);
2189 if (mean_image == (Image *) NULL)
2190 return((Image *) NULL);
2191 if (SetImageStorageClass(mean_image,DirectClass,exception) == MagickFalse)
2192 {
2193 mean_image=DestroyImage(mean_image);
2194 return((Image *) NULL);
2195 }
2196 status=MagickTrue;
2197 progress=0;
2198 image_view=AcquireVirtualCacheView(image,exception);
2199 pixel_view=AcquireVirtualCacheView(image,exception);
2200 mean_view=AcquireAuthenticCacheView(mean_image,exception);
2201#if defined(MAGICKCORE_OPENMP_SUPPORT)
2202 #pragma omp parallel for schedule(static) shared(status,progress) \
2203 magick_number_threads(mean_image,mean_image,mean_image->rows,1)
2204#endif
2205 for (y=0; y < (ssize_t) mean_image->rows; y++)
2206 {
2207 const Quantum
2208 *magick_restrict p;
2209
2210 Quantum
2211 *magick_restrict q;
2212
2213 ssize_t
2214 x;
2215
2216 if (status == MagickFalse)
2217 continue;
2218 p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
2219 q=GetCacheViewAuthenticPixels(mean_view,0,y,mean_image->columns,1,
2220 exception);
2221 if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
2222 {
2223 status=MagickFalse;
2224 continue;
2225 }
2226 for (x=0; x < (ssize_t) mean_image->columns; x++)
2227 {
2228 PixelInfo
2229 mean_pixel,
2230 previous_pixel;
2231
2232 PointInfo
2233 mean_location,
2234 previous_location;
2235
2236 ssize_t
2237 i;
2238
2239 GetPixelInfo(image,&mean_pixel);
2240 GetPixelInfoPixel(image,p,&mean_pixel);
2241 mean_location.x=(double) x;
2242 mean_location.y=(double) y;
2243 for (i=0; i < MaxMeanShiftIterations; i++)
2244 {
2245 double
2246 distance,
2247 gamma = 1.0;
2248
2249 PixelInfo
2250 sum_pixel;
2251
2252 PointInfo
2253 sum_location;
2254
2255 ssize_t
2256 count,
2257 v;
2258
2259 sum_location.x=0.0;
2260 sum_location.y=0.0;
2261 GetPixelInfo(image,&sum_pixel);
2262 previous_location=mean_location;
2263 previous_pixel=mean_pixel;
2264 count=0;
2265 for (v=(-((ssize_t) height/2)); v <= (((ssize_t) height/2)); v++)
2266 {
2267 ssize_t
2268 u;
2269
2270 for (u=(-((ssize_t) width/2)); u <= (((ssize_t) width/2)); u++)
2271 {
2272 if ((v*v+u*u) <= (ssize_t) ((width/2)*(height/2)))
2273 {
2274 PixelInfo
2275 pixel;
2276
2277 status=GetOneCacheViewVirtualPixelInfo(pixel_view,(ssize_t)
2278 MagickRound(mean_location.x+u),(ssize_t) MagickRound(
2279 mean_location.y+v),&pixel,exception);
2280 distance=(mean_pixel.red-pixel.red)*(mean_pixel.red-pixel.red)+
2281 (mean_pixel.green-pixel.green)*(mean_pixel.green-pixel.green)+
2282 (mean_pixel.blue-pixel.blue)*(mean_pixel.blue-pixel.blue);
2283 if (distance <= (color_distance*color_distance))
2284 {
2285 sum_location.x+=mean_location.x+u;
2286 sum_location.y+=mean_location.y+v;
2287 sum_pixel.red+=pixel.red;
2288 sum_pixel.green+=pixel.green;
2289 sum_pixel.blue+=pixel.blue;
2290 sum_pixel.alpha+=pixel.alpha;
2291 count++;
2292 }
2293 }
2294 }
2295 }
2296 if (count != 0)
2297 gamma=MagickSafeReciprocal((double) count);
2298 mean_location.x=gamma*sum_location.x;
2299 mean_location.y=gamma*sum_location.y;
2300 mean_pixel.red=gamma*sum_pixel.red;
2301 mean_pixel.green=gamma*sum_pixel.green;
2302 mean_pixel.blue=gamma*sum_pixel.blue;
2303 mean_pixel.alpha=gamma*sum_pixel.alpha;
2304 distance=(mean_location.x-previous_location.x)*
2305 (mean_location.x-previous_location.x)+
2306 (mean_location.y-previous_location.y)*
2307 (mean_location.y-previous_location.y)+
2308 255.0*QuantumScale*(mean_pixel.red-previous_pixel.red)*
2309 255.0*QuantumScale*(mean_pixel.red-previous_pixel.red)+
2310 255.0*QuantumScale*(mean_pixel.green-previous_pixel.green)*
2311 255.0*QuantumScale*(mean_pixel.green-previous_pixel.green)+
2312 255.0*QuantumScale*(mean_pixel.blue-previous_pixel.blue)*
2313 255.0*QuantumScale*(mean_pixel.blue-previous_pixel.blue);
2314 if (distance <= 3.0)
2315 break;
2316 }
2317 SetPixelRed(mean_image,ClampToQuantum(mean_pixel.red),q);
2318 SetPixelGreen(mean_image,ClampToQuantum(mean_pixel.green),q);
2319 SetPixelBlue(mean_image,ClampToQuantum(mean_pixel.blue),q);
2320 SetPixelAlpha(mean_image,ClampToQuantum(mean_pixel.alpha),q);
2321 p+=(ptrdiff_t) GetPixelChannels(image);
2322 q+=(ptrdiff_t) GetPixelChannels(mean_image);
2323 }
2324 if (SyncCacheViewAuthenticPixels(mean_view,exception) == MagickFalse)
2325 status=MagickFalse;
2326 if (image->progress_monitor != (MagickProgressMonitor) NULL)
2327 {
2328 MagickBooleanType
2329 proceed;
2330
2331#if defined(MAGICKCORE_OPENMP_SUPPORT)
2332 #pragma omp atomic
2333#endif
2334 progress++;
2335 proceed=SetImageProgress(image,MeanShiftImageTag,progress,image->rows);
2336 if (proceed == MagickFalse)
2337 status=MagickFalse;
2338 }
2339 }
2340 mean_view=DestroyCacheView(mean_view);
2341 pixel_view=DestroyCacheView(pixel_view);
2342 image_view=DestroyCacheView(image_view);
2343 return(mean_image);
2344}