vigra - vigra/edgedetection.hxx Source File

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edgedetection.hxx |

1 /************************************************************************/
2 /* */
3 /* Copyright 1998-2002 by Ullrich Koethe */
4 /* */
5 /* This file is part of the VIGRA computer vision library. */
6 /* The VIGRA Website is */
7 /* http://hci.iwr.uni-heidelberg.de/vigra/ */
8 /* Please direct questions, bug reports, and contributions to */
9 /* ullrich.koethe@iwr.uni-heidelberg.de or */
10 /* vigra@informatik.uni-hamburg.de */
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13 /* obtaining a copy of this software and associated documentation */
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35
36
37 #ifndef VIGRA_EDGEDETECTION_HXX
38 #define VIGRA_EDGEDETECTION_HXX
39
40 #include <vector>
41 #include <queue>
42 #include <cmath> // sqrt(), abs()
43 #include "utilities.hxx"
44 #include "numerictraits.hxx"
45 #include "stdimage.hxx"
46 #include "stdimagefunctions.hxx"
47 #include "recursiveconvolution.hxx"
48 #include "separableconvolution.hxx"
49 #include "convolution.hxx"
50 #include "labelimage.hxx"
51 #include "mathutil.hxx"
52 #include "pixelneighborhood.hxx"
53 #include "linear_solve.hxx"
54 #include "functorexpression.hxx"
55 #include "multi_shape.hxx"
56
57 namespace vigra {
58
59 /** \addtogroup EdgeDetection Edge Detection
60 Edge detectors based on first and second derivatives,
61 and related post-processing.
62 */
63 //@{
64
65 /********************************************************/
66 /* */
67 /* differenceOfExponentialEdgeImage */
68 /* */
69 /********************************************************/
70
71 /** \brief Detect and mark edges in an edge image using the Shen/Castan zero-crossing detector.
72
73 This operator applies an exponential filter to the source image
74 at the given <TT>scale</TT> and subtracts the result from the original image.
75 Zero crossings are detected in the resulting difference image. Whenever the
76 gradient at a zero crossing is greater than the given <TT>gradient_threshold</TT>,
77 an edge point is marked (using <TT>edge_marker</TT>) in the destination image on
78 the darker side of the zero crossing (note that zero crossings occur
79 <i>between</i> pixels). For example:
80
81 \code
82 sign of difference image resulting edge points (*)
83
84 + - - * * .
85 + + - => . * *
86 + + + . . .
87 \endcode
88
89 Non-edge pixels (<TT>.</TT>) remain untouched in the destination image.
90 The result can be improved by the post-processing operation \ref removeShortEdges().
91 A more accurate edge placement can be achieved with the function
92 \ref differenceOfExponentialCrackEdgeImage().
93
94 The source value type
95 (<TT>SrcAccessor::value_type</TT>) must be a linear algebra, i.e. addition,
96 subtraction and multiplication of the type with itself, and multiplication
97 with double and
98 \ref NumericTraits "NumericTraits" must
99 be defined. In addition, this type must be less-comparable.
100
101 <b> Declarations:</b>
102
103 pass 2D array views:
104 \code
105 namespace vigra {
106 template <class T1, class S1,
107 class T2, class S2,
108 class GradValue, class DestValue>
109 void
110 differenceOfExponentialEdgeImage(MultiArrayView<2, T1, S1> const & src,
111 MultiArrayView<2, T2, S2> dest,
112 double scale,
113 GradValue gradient_threshold,
114 DestValue edge_marker = NumericTraits<DestValue>::one());
115 }
116 \endcode
117
118 \deprecatedAPI{differenceOfExponentialEdgeImage}
119 pass \ref ImageIterators and \ref DataAccessors :
120 \code
121 namespace vigra {
122 template <class SrcIterator, class SrcAccessor,
123 class DestIterator, class DestAccessor,
124 class GradValue,
125 class DestValue = DestAccessor::value_type>
126 void differenceOfExponentialEdgeImage(
127 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
128 DestIterator dul, DestAccessor da,
129 double scale, GradValue gradient_threshold,
130 DestValue edge_marker = NumericTraits<DestValue>::one())
131 }
132 \endcode
133 use argument objects in conjunction with \ref ArgumentObjectFactories :
134 \code
135 namespace vigra {
136 template <class SrcIterator, class SrcAccessor,
137 class DestIterator, class DestAccessor,
138 class GradValue,
139 class DestValue = DestAccessor::value_type>
140 void differenceOfExponentialEdgeImage(
141 triple<SrcIterator, SrcIterator, SrcAccessor> src,
142 pair<DestIterator, DestAccessor> dest,
143 double scale, GradValue gradient_threshold,
144 DestValue edge_marker = NumericTraits<DestValue>::one())
145 }
146 \endcode
147 \deprecatedEnd
148
149 <b> Usage:</b>
150
151 <b>\#include</b> <vigra/edgedetection.hxx><br>
152 Namespace: vigra
153
154 \code
155 MultiArray<2, unsigned char> src(w,h), edges(w,h);
156 ...
157
158 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
159 differenceOfExponentialEdgeImage(src, edges,
160 0.8, 4.0, 1);
161 \endcode
162
163 \deprecatedUsage{differenceOfExponentialEdgeImage}
164 \code
165 vigra::BImage src(w,h), edges(w,h);
166
167 // empty edge image
168 edges = 0;
169 ...
170
171 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
172 vigra::differenceOfExponentialEdgeImage(srcImageRange(src), destImage(edges),
173 0.8, 4.0, 1);
174 \endcode
175 <b> Required Interface:</b>
176 \code
177 SrcImageIterator src_upperleft, src_lowerright;
178 DestImageIterator dest_upperleft;
179
180 SrcAccessor src_accessor;
181 DestAccessor dest_accessor;
182
183 SrcAccessor::value_type u = src_accessor(src_upperleft);
184 double d;
185 GradValue gradient_threshold;
186
187 u = u + u
188 u = u - u
189 u = u * u
190 u = d * u
191 u < gradient_threshold
192
193 DestValue edge_marker;
194 dest_accessor.set(edge_marker, dest_upperleft);
195 \endcode
196 \deprecatedEnd
197
198 <b> Preconditions:</b>
199
200 \code
201 scale > 0
202 gradient_threshold > 0
203 \endcode
204 */
205 doxygen_overloaded_function(template <...> void differenceOfExponentialEdgeImage)
206
207 template <class SrcIterator, class SrcAccessor,
208 class DestIterator, class DestAccessor,
209 class GradValue, class DestValue>
210 void differenceOfExponentialEdgeImage(
211 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
212 DestIterator dul, DestAccessor da,
213 double scale, GradValue gradient_threshold, DestValue edge_marker)
214 {
215 vigra_precondition(scale > 0,
216 "differenceOfExponentialEdgeImage(): scale > 0 required.");
217
218 vigra_precondition(gradient_threshold > 0,
219 "differenceOfExponentialEdgeImage(): "
220 "gradient_threshold > 0 required.");
221
222 int w = slr.x - sul.x;
223 int h = slr.y - sul.y;
224 int x,y;
225
226 typedef typename
227 NumericTraits<typename SrcAccessor::value_type>::RealPromote
228 TMPTYPE;
229 typedef BasicImage<TMPTYPE> TMPIMG;
230
231 TMPIMG tmp(w,h);
232 TMPIMG smooth(w,h);
233
234 recursiveSmoothX(srcIterRange(sul, slr, sa), destImage(tmp), scale / 2.0);
235 recursiveSmoothY(srcImageRange(tmp), destImage(tmp), scale / 2.0);
236
237 recursiveSmoothX(srcImageRange(tmp), destImage(smooth), scale);
238 recursiveSmoothY(srcImageRange(smooth), destImage(smooth), scale);
239
240 typename TMPIMG::Iterator iy = smooth.upperLeft();
241 typename TMPIMG::Iterator ty = tmp.upperLeft();
242 DestIterator dy = dul;
243
244 const Diff2D right(1, 0);
245 const Diff2D bottom(0, 1);
246
247
248 TMPTYPE thresh = detail::RequiresExplicitCast<TMPTYPE>::cast((gradient_threshold * gradient_threshold) *
249 NumericTraits<TMPTYPE>::one());
250 TMPTYPE zero = NumericTraits<TMPTYPE>::zero();
251
252 for(y=0; y<h-1; ++y, ++iy.y, ++ty.y, ++dy.y)
253 {
254 typename TMPIMG::Iterator ix = iy;
255 typename TMPIMG::Iterator tx = ty;
256 DestIterator dx = dy;
257
258 for(x=0; x<w-1; ++x, ++ix.x, ++tx.x, ++dx.x)
259 {
260 TMPTYPE diff = *tx - *ix;
261 TMPTYPE gx = tx[right] - *tx;
262 TMPTYPE gy = tx[bottom] - *tx;
263
264 if((gx * gx > thresh) &&
265 (diff * (tx[right] - ix[right]) < zero))
266 {
267 if(gx < zero)
268 {
269 da.set(edge_marker, dx, right);
270 }
271 else
272 {
273 da.set(edge_marker, dx);
274 }
275 }
276 if(((gy * gy > thresh) &&
277 (diff * (tx[bottom] - ix[bottom]) < zero)))
278 {
279 if(gy < zero)
280 {
281 da.set(edge_marker, dx, bottom);
282 }
283 else
284 {
285 da.set(edge_marker, dx);
286 }
287 }
288 }
289 }
290
291 typename TMPIMG::Iterator ix = iy;
292 typename TMPIMG::Iterator tx = ty;
293 DestIterator dx = dy;
294
295 for(x=0; x<w-1; ++x, ++ix.x, ++tx.x, ++dx.x)
296 {
297 TMPTYPE diff = *tx - *ix;
298 TMPTYPE gx = tx[right] - *tx;
299
300 if((gx * gx > thresh) &&
301 (diff * (tx[right] - ix[right]) < zero))
302 {
303 if(gx < zero)
304 {
305 da.set(edge_marker, dx, right);
306 }
307 else
308 {
309 da.set(edge_marker, dx);
310 }
311 }
312 }
313 }
314
315 template <class SrcIterator, class SrcAccessor,
316 class DestIterator, class DestAccessor,
317 class GradValue>
318 inline
319 void differenceOfExponentialEdgeImage(
320 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
321 DestIterator dul, DestAccessor da,
322 double scale, GradValue gradient_threshold)
323 {
324 differenceOfExponentialEdgeImage(sul, slr, sa, dul, da,
325 scale, gradient_threshold, 1);
326 }
327
328 template <class SrcIterator, class SrcAccessor,
329 class DestIterator, class DestAccessor,
330 class GradValue, class DestValue>
331 inline void
332 differenceOfExponentialEdgeImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
333 pair<DestIterator, DestAccessor> dest,
334 double scale, GradValue gradient_threshold,
335 DestValue edge_marker)
336 {
337 differenceOfExponentialEdgeImage(src.first, src.second, src.third,
338 dest.first, dest.second,
339 scale, gradient_threshold, edge_marker);
340 }
341
342 template <class SrcIterator, class SrcAccessor,
343 class DestIterator, class DestAccessor,
344 class GradValue>
345 inline void
346 differenceOfExponentialEdgeImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
347 pair<DestIterator, DestAccessor> dest,
348 double scale, GradValue gradient_threshold)
349 {
350 differenceOfExponentialEdgeImage(src.first, src.second, src.third,
351 dest.first, dest.second,
352 scale, gradient_threshold, 1);
353 }
354
355 template <class T1, class S1,
356 class T2, class S2,
357 class GradValue, class DestValue>
358 inline void
359 differenceOfExponentialEdgeImage(MultiArrayView<2, T1, S1> const & src,
360 MultiArrayView<2, T2, S2> dest,
361 double scale,
362 GradValue gradient_threshold,
363 DestValue edge_marker)
364 {
365 vigra_precondition(src.shape() == dest.shape(),
366 "differenceOfExponentialEdgeImage(): shape mismatch between input and output.");
367 differenceOfExponentialEdgeImage(srcImageRange(src),
368 destImage(dest),
369 scale, gradient_threshold, edge_marker);
370 }
371
372 template <class T1, class S1,
373 class T2, class S2,
374 class GradValue>
375 inline void
376 differenceOfExponentialEdgeImage(MultiArrayView<2, T1, S1> const & src,
377 MultiArrayView<2, T2, S2> dest,
378 double scale, GradValue gradient_threshold)
379 {
380 vigra_precondition(src.shape() == dest.shape(),
381 "differenceOfExponentialEdgeImage(): shape mismatch between input and output.");
382 differenceOfExponentialEdgeImage(srcImageRange(src),
383 destImage(dest),
384 scale, gradient_threshold, T2(1));
385 }
386
387 /********************************************************/
388 /* */
389 /* differenceOfExponentialCrackEdgeImage */
390 /* */
391 /********************************************************/
392
393 /** \brief Detect and mark edges in a crack edge image using the Shen/Castan zero-crossing detector.
394
395 This operator applies an exponential filter to the source image
396 at the given <TT>scale</TT> and subtracts the result from the original image.
397 Zero crossings are detected in the resulting difference image. Whenever the
398 gradient at a zero crossing is greater than the given <TT>gradient_threshold</TT>,
399 an edge point is marked (using <TT>edge_marker</TT>) in the destination image
400 <i>between</i> the corresponding original pixels. Topologically, this means we
401 must insert additional pixels between the original ones to represent the
402 boundaries between the pixels (the so called zero- and one-cells, with the original
403 pixels being two-cells). Within VIGRA, such an image is called \ref CrackEdgeImage.
404 To allow insertion of the zero- and one-cells, the destination image must have twice the
405 size of the original (precisely, <TT>(2*w-1)</TT> by <TT>(2*h-1)</TT> pixels). Then the algorithm
406 proceeds as follows:
407
408 \code
409 sign of difference image insert zero- and one-cells resulting edge points (*)
410
411 + . - . - . * . . .
412 + - - . . . . . . * * * .
413 + + - => + . + . - => . . . * .
414 + + + . . . . . . . . * *
415 + . + . + . . . . .
416 \endcode
417
418 Thus the edge points are marked where they actually are - in between the pixels.
419 An important property of the resulting edge image is that it conforms to the notion
420 of well-composedness as defined by Latecki et al., i.e. connected regions and edges
421 obtained by a subsequent \ref Labeling do not depend on
422 whether 4- or 8-connectivity is used.
423 The non-edge pixels (<TT>.</TT>) in the destination image remain unchanged.
424 The result conforms to the requirements of a \ref CrackEdgeImage. It can be further
425 improved by the post-processing operations \ref removeShortEdges() and
426 \ref closeGapsInCrackEdgeImage().
427
428 The source value type (<TT>SrcAccessor::value_type</TT>) must be a linear algebra, i.e. addition,
429 subtraction and multiplication of the type with itself, and multiplication
430 with double and
431 \ref NumericTraits "NumericTraits" must
432 be defined. In addition, this type must be less-comparable.
433
434 <b> Declarations:</b>
435
436 pass 2D array views:
437 \code
438 namespace vigra {
439 template <class T1, class S1,
440 class T2, class S2,
441 class GradValue, class DestValue>
442 void
443 differenceOfExponentialCrackEdgeImage(MultiArrayView<2, T1, S1> const & src,
444 MultiArrayView<2, T2, S2> dest,
445 double scale,
446 GradValue gradient_threshold,
447 DestValue edge_marker = NumericTraits<DestValue>::one());
448 }
449 \endcode
450
451 \deprecatedAPI{differenceOfExponentialCrackEdgeImage}
452 pass \ref ImageIterators and \ref DataAccessors :
453 \code
454 namespace vigra {
455 template <class SrcIterator, class SrcAccessor,
456 class DestIterator, class DestAccessor,
457 class GradValue,
458 class DestValue = DestAccessor::value_type>
459 void differenceOfExponentialCrackEdgeImage(
460 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
461 DestIterator dul, DestAccessor da,
462 double scale, GradValue gradient_threshold,
463 DestValue edge_marker = NumericTraits<DestValue>::one())
464 }
465 \endcode
466 use argument objects in conjunction with \ref ArgumentObjectFactories :
467 \code
468 namespace vigra {
469 template <class SrcIterator, class SrcAccessor,
470 class DestIterator, class DestAccessor,
471 class GradValue,
472 class DestValue = DestAccessor::value_type>
473 void differenceOfExponentialCrackEdgeImage(
474 triple<SrcIterator, SrcIterator, SrcAccessor> src,
475 pair<DestIterator, DestAccessor> dest,
476 double scale, GradValue gradient_threshold,
477 DestValue edge_marker = NumericTraits<DestValue>::one())
478 }
479 \endcode
480 \deprecatedEnd
481
482 <b> Usage:</b>
483
484 <b>\#include</b> <vigra/edgedetection.hxx><br>
485 Namespace: vigra
486
487 \code
488 MultiArray<2, unsigned char> src(w,h), edges(2*w-1,2*h-1);
489 ...
490
491 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
492 differenceOfExponentialCrackEdgeImage(src, edges,
493 0.8, 4.0, 1);
494 \endcode
495
496 \deprecatedUsage{differenceOfExponentialCrackEdgeImage}
497 \code
498 vigra::BImage src(w,h), edges(2*w-1,2*h-1);
499
500 // empty edge image
501 edges = 0;
502 ...
503
504 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
505 vigra::differenceOfExponentialCrackEdgeImage(srcImageRange(src), destImage(edges),
506 0.8, 4.0, 1);
507 \endcode
508 <b> Required Interface:</b>
509 \code
510 SrcImageIterator src_upperleft, src_lowerright;
511 DestImageIterator dest_upperleft;
512
513 SrcAccessor src_accessor;
514 DestAccessor dest_accessor;
515
516 SrcAccessor::value_type u = src_accessor(src_upperleft);
517 double d;
518 GradValue gradient_threshold;
519
520 u = u + u
521 u = u - u
522 u = u * u
523 u = d * u
524 u < gradient_threshold
525
526 DestValue edge_marker;
527 dest_accessor.set(edge_marker, dest_upperleft);
528 \endcode
529 \deprecatedEnd
530
531 <b> Preconditions:</b>
532
533 \code
534 scale > 0
535 gradient_threshold > 0
536 \endcode
537
538 The destination image must have twice the size of the source:
539 \code
540 w_dest = 2 * w_src - 1
541 h_dest = 2 * h_src - 1
542 \endcode
543 */
544 doxygen_overloaded_function(template <...> void differenceOfExponentialCrackEdgeImage)
545
546 template <class SrcIterator, class SrcAccessor,
547 class DestIterator, class DestAccessor,
548 class GradValue, class DestValue>
549 void differenceOfExponentialCrackEdgeImage(
550 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
551 DestIterator dul, DestAccessor da,
552 double scale, GradValue gradient_threshold,
553 DestValue edge_marker)
554 {
555 vigra_precondition(scale > 0,
556 "differenceOfExponentialCrackEdgeImage(): scale > 0 required.");
557
558 vigra_precondition(gradient_threshold > 0,
559 "differenceOfExponentialCrackEdgeImage(): "
560 "gradient_threshold > 0 required.");
561
562 int w = slr.x - sul.x;
563 int h = slr.y - sul.y;
564 int x, y;
565
566 typedef typename
567 NumericTraits<typename SrcAccessor::value_type>::RealPromote
568 TMPTYPE;
569 typedef BasicImage<TMPTYPE> TMPIMG;
570
571 TMPIMG tmp(w,h);
572 TMPIMG smooth(w,h);
573
574 TMPTYPE zero = NumericTraits<TMPTYPE>::zero();
575
576 const Diff2D right(1,0);
577 const Diff2D bottom(0,1);
578 const Diff2D left(-1,0);
579 const Diff2D top(0,-1);
580
581 recursiveSmoothX(srcIterRange(sul, slr, sa), destImage(tmp), scale / 2.0);
582 recursiveSmoothY(srcImageRange(tmp), destImage(tmp), scale / 2.0);
583
584 recursiveSmoothX(srcImageRange(tmp), destImage(smooth), scale);
585 recursiveSmoothY(srcImageRange(smooth), destImage(smooth), scale);
586
587 typename TMPIMG::Iterator iy = smooth.upperLeft();
588 typename TMPIMG::Iterator ty = tmp.upperLeft();
589 DestIterator dy = dul;
590
591 TMPTYPE thresh = detail::RequiresExplicitCast<TMPTYPE>::cast((gradient_threshold * gradient_threshold) *
592 NumericTraits<TMPTYPE>::one());
593
594 // find zero crossings above threshold
595 for(y=0; y<h-1; ++y, ++iy.y, ++ty.y, dy.y+=2)
596 {
597 typename TMPIMG::Iterator ix = iy;
598 typename TMPIMG::Iterator tx = ty;
599 DestIterator dx = dy;
600
601 for(int x=0; x<w-1; ++x, ++ix.x, ++tx.x, dx.x+=2)
602 {
603 TMPTYPE diff = *tx - *ix;
604 TMPTYPE gx = tx[right] - *tx;
605 TMPTYPE gy = tx[bottom] - *tx;
606
607 if((gx * gx > thresh) &&
608 (diff * (tx[right] - ix[right]) < zero))
609 {
610 da.set(edge_marker, dx, right);
611 }
612 if((gy * gy > thresh) &&
613 (diff * (tx[bottom] - ix[bottom]) < zero))
614 {
615 da.set(edge_marker, dx, bottom);
616 }
617 }
618
619 TMPTYPE diff = *tx - *ix;
620 TMPTYPE gy = tx[bottom] - *tx;
621
622 if((gy * gy > thresh) &&
623 (diff * (tx[bottom] - ix[bottom]) < zero))
624 {
625 da.set(edge_marker, dx, bottom);
626 }
627 }
628
629 typename TMPIMG::Iterator ix = iy;
630 typename TMPIMG::Iterator tx = ty;
631 DestIterator dx = dy;
632
633 for(x=0; x<w-1; ++x, ++ix.x, ++tx.x, dx.x+=2)
634 {
635 TMPTYPE diff = *tx - *ix;
636 TMPTYPE gx = tx[right] - *tx;
637
638 if((gx * gx > thresh) &&
639 (diff * (tx[right] - ix[right]) < zero))
640 {
641 da.set(edge_marker, dx, right);
642 }
643 }
644
645 iy = smooth.upperLeft() + Diff2D(0,1);
646 ty = tmp.upperLeft() + Diff2D(0,1);
647 dy = dul + Diff2D(1,2);
648
649 const Diff2D topleft(-1,-1);
650 const Diff2D topright(1,-1);
651 const Diff2D bottomleft(-1,1);
652 const Diff2D bottomright(1,1);
653
654 // find missing 1-cells below threshold (x-direction)
655 for(y=0; y<h-2; ++y, ++iy.y, ++ty.y, dy.y+=2)
656 {
657 typename TMPIMG::Iterator ix = iy;
658 typename TMPIMG::Iterator tx = ty;
659 DestIterator dx = dy;
660
661 for(int x=0; x<w-2; ++x, ++ix.x, ++tx.x, dx.x+=2)
662 {
663 if(da(dx) == edge_marker) continue;
664
665 TMPTYPE diff = *tx - *ix;
666
667 if((diff * (tx[right] - ix[right]) < zero) &&
668 (((da(dx, bottomright) == edge_marker) &&
669 (da(dx, topleft) == edge_marker)) ||
670 ((da(dx, bottomleft) == edge_marker) &&
671 (da(dx, topright) == edge_marker))))
672
673 {
674 da.set(edge_marker, dx);
675 }
676 }
677 }
678
679 iy = smooth.upperLeft() + Diff2D(1,0);
680 ty = tmp.upperLeft() + Diff2D(1,0);
681 dy = dul + Diff2D(2,1);
682
683 // find missing 1-cells below threshold (y-direction)
684 for(y=0; y<h-2; ++y, ++iy.y, ++ty.y, dy.y+=2)
685 {
686 typename TMPIMG::Iterator ix = iy;
687 typename TMPIMG::Iterator tx = ty;
688 DestIterator dx = dy;
689
690 for(int x=0; x<w-2; ++x, ++ix.x, ++tx.x, dx.x+=2)
691 {
692 if(da(dx) == edge_marker) continue;
693
694 TMPTYPE diff = *tx - *ix;
695
696 if((diff * (tx[bottom] - ix[bottom]) < zero) &&
697 (((da(dx, bottomright) == edge_marker) &&
698 (da(dx, topleft) == edge_marker)) ||
699 ((da(dx, bottomleft) == edge_marker) &&
700 (da(dx, topright) == edge_marker))))
701
702 {
703 da.set(edge_marker, dx);
704 }
705 }
706 }
707
708 dy = dul + Diff2D(1,1);
709
710 // find missing 0-cells
711 for(y=0; y<h-1; ++y, dy.y+=2)
712 {
713 DestIterator dx = dy;
714
715 for(int x=0; x<w-1; ++x, dx.x+=2)
716 {
717 const Diff2D dist[] = {right, top, left, bottom };
718
719 int i;
720 for(i=0; i<4; ++i)
721 {
722 if(da(dx, dist[i]) == edge_marker) break;
723 }
724
725 if(i < 4) da.set(edge_marker, dx);
726 }
727 }
728 }
729
730 template <class SrcIterator, class SrcAccessor,
731 class DestIterator, class DestAccessor,
732 class GradValue, class DestValue>
733 inline void
734 differenceOfExponentialCrackEdgeImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
735 pair<DestIterator, DestAccessor> dest,
736 double scale, GradValue gradient_threshold,
737 DestValue edge_marker)
738 {
739 differenceOfExponentialCrackEdgeImage(src.first, src.second, src.third,
740 dest.first, dest.second,
741 scale, gradient_threshold, edge_marker);
742 }
743
744 template <class T1, class S1,
745 class T2, class S2,
746 class GradValue, class DestValue>
747 inline void
748 differenceOfExponentialCrackEdgeImage(MultiArrayView<2, T1, S1> const & src,
749 MultiArrayView<2, T2, S2> dest,
750 double scale,
751 GradValue gradient_threshold,
752 DestValue edge_marker)
753 {
754 vigra_precondition(2*src.shape() - Shape2(1) == dest.shape(),
755 "differenceOfExponentialCrackEdgeImage(): shape mismatch between input and output.");
756 differenceOfExponentialCrackEdgeImage(srcImageRange(src),
757 destImage(dest),
758 scale, gradient_threshold, edge_marker);
759 }
760
761 /********************************************************/
762 /* */
763 /* removeShortEdges */
764 /* */
765 /********************************************************/
766
767 /** \brief Remove short edges from an edge image.
768
769 This algorithm can be applied as a post-processing operation of
770 \ref differenceOfExponentialEdgeImage() and \ref differenceOfExponentialCrackEdgeImage().
771 It removes all edges that are shorter than <TT>min_edge_length</TT>. The corresponding
772 pixels are set to the <TT>non_edge_marker</TT>. The idea behind this algorithms is
773 that very short edges are probably caused by noise and don't represent interesting
774 image structure. Technically, the algorithms executes a connected components labeling,
775 so the image's value type must be equality comparable.
776
777 If the source image fulfills the requirements of a \ref CrackEdgeImage,
778 it will still do so after application of this algorithm.
779
780 Note that this algorithm, unlike most other algorithms in VIGRA, operates in-place,
781 i.e. on only one image. Also, the algorithm assumes that all non-edges pixels are already
782 marked with the given <TT>non_edge_marker</TT> value.
783
784 <b> Declarations:</b>
785
786 pass 2D array views:
787 \code
788 namespace vigra {
789 template <class T, class S, class Value>
790 void
791 removeShortEdges(MultiArrayView<2, T, S> image,
792 unsigned int min_edge_length, Value non_edge_marker);
793 }
794 \endcode
795
796 \deprecatedAPI{removeShortEdges}
797 pass \ref ImageIterators and \ref DataAccessors :
798 \code
799 namespace vigra {
800 template <class Iterator, class Accessor, class SrcValue>
801 void removeShortEdges(
802 Iterator sul, Iterator slr, Accessor sa,
803 int min_edge_length, SrcValue non_edge_marker)
804 }
805 \endcode
806 use argument objects in conjunction with \ref ArgumentObjectFactories :
807 \code
808 namespace vigra {
809 template <class Iterator, class Accessor, class SrcValue>
810 void removeShortEdges(
811 triple<Iterator, Iterator, Accessor> src,
812 int min_edge_length, SrcValue non_edge_marker)
813 }
814 \endcode
815 \deprecatedEnd
816
817 <b> Usage:</b>
818
819 <b>\#include</b> <vigra/edgedetection.hxx><br>
820 Namespace: vigra
821
822 \code
823 MultiArray<2, unsigned char> src(w,h), edges(w,h);
824 ...
825
826 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
827 differenceOfExponentialEdgeImage(src, edges,
828 0.8, 4.0, 1);
829
830 // zero edges shorter than 10 pixels
831 removeShortEdges(edges, 10, 0);
832 \endcode
833
834 \deprecatedUsage{removeShortEdges}
835 \code
836 vigra::BImage src(w,h), edges(w,h);
837
838 // empty edge image
839 edges = 0;
840 ...
841
842 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
843 vigra::differenceOfExponentialEdgeImage(srcImageRange(src), destImage(edges),
844 0.8, 4.0, 1);
845
846 // zero edges shorter than 10 pixels
847 vigra::removeShortEdges(srcImageRange(edges), 10, 0);
848 \endcode
849 <b> Required Interface:</b>
850 \code
851 SrcImageIterator src_upperleft, src_lowerright;
852 DestImageIterator dest_upperleft;
853
854 SrcAccessor src_accessor;
855 DestAccessor dest_accessor;
856
857 SrcAccessor::value_type u = src_accessor(src_upperleft);
858
859 u == u
860
861 SrcValue non_edge_marker;
862 src_accessor.set(non_edge_marker, src_upperleft);
863 \endcode
864 \deprecatedEnd
865 */
866 doxygen_overloaded_function(template <...> void removeShortEdges)
867
868 template <class Iterator, class Accessor, class Value>
869 void removeShortEdges(
870 Iterator sul, Iterator slr, Accessor sa,
871 unsigned int min_edge_length, Value non_edge_marker)
872 {
873 int w = slr.x - sul.x;
874 int h = slr.y - sul.y;
875 int x,y;
876
877 IImage labels(w, h);
878 labels = 0;
879
880 int number_of_regions =
881 labelImageWithBackground(srcIterRange(sul,slr,sa),
882 destImage(labels), true, non_edge_marker);
883
884 ArrayOfRegionStatistics<FindROISize<int> >
885 region_stats(number_of_regions);
886
887 inspectTwoImages(srcImageRange(labels), srcImage(labels), region_stats);
888
889 IImage::Iterator ly = labels.upperLeft();
890 Iterator oy = sul;
891
892 for(y=0; y<h; ++y, ++oy.y, ++ly.y)
893 {
894 Iterator ox(oy);
895 IImage::Iterator lx(ly);
896
897 for(x=0; x<w; ++x, ++ox.x, ++lx.x)
898 {
899 if(sa(ox) == non_edge_marker) continue;
900 if((region_stats[*lx].count) < min_edge_length)
901 {
902 sa.set(non_edge_marker, ox);
903 }
904 }
905 }
906 }
907
908 template <class Iterator, class Accessor, class Value>
909 inline void
910 removeShortEdges(triple<Iterator, Iterator, Accessor> src,
911 unsigned int min_edge_length, Value non_edge_marker)
912 {
913 removeShortEdges(src.first, src.second, src.third,
914 min_edge_length, non_edge_marker);
915 }
916
917 template <class T, class S, class Value>
918 inline void
919 removeShortEdges(MultiArrayView<2, T, S> image,
920 unsigned int min_edge_length, Value non_edge_marker)
921 {
922 removeShortEdges(destImageRange(image),
923 min_edge_length, non_edge_marker);
924 }
925
926 /********************************************************/
927 /* */
928 /* closeGapsInCrackEdgeImage */
929 /* */
930 /********************************************************/
931
932 /** \brief Close one-pixel wide gaps in a cell grid edge image.
933
934 This algorithm is typically applied as a post-processing operation of
935 \ref differenceOfExponentialCrackEdgeImage(). The source image must fulfill
936 the requirements of a \ref CrackEdgeImage, and will still do so after
937 application of this algorithm.
938
939 It closes one pixel wide gaps in the edges resulting from this algorithm.
940 Since these gaps are usually caused by zero crossing slightly below the gradient
941 threshold used in edge detection, this algorithms acts like a weak hysteresis
942 thresholding. The newly found edge pixels are marked with the given <TT>edge_marker</TT>.
943 The image's value type must be equality comparable.
944
945 Note that this algorithm, unlike most other algorithms in VIGRA, operates in-place,
946 i.e. on only one image.
947
948 <b> Declarations:</b>
949
950 pass 2D array views:
951 \code
952 namespace vigra {
953 template <class T, class S, class Value>
954 void
955 closeGapsInCrackEdgeImage(MultiArrayView<2, T, S> image, Value edge_marker);
956 }
957 \endcode
958
959 \deprecatedAPI{closeGapsInCrackEdgeImage}
960 pass \ref ImageIterators and \ref DataAccessors :
961 \code
962 namespace vigra {
963 template <class SrcIterator, class SrcAccessor, class SrcValue>
964 void closeGapsInCrackEdgeImage(
965 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
966 SrcValue edge_marker)
967 }
968 \endcode
969 use argument objects in conjunction with \ref ArgumentObjectFactories :
970 \code
971 namespace vigra {
972 template <class SrcIterator, class SrcAccessor, class SrcValue>
973 void closeGapsInCrackEdgeImage(
974 triple<SrcIterator, SrcIterator, SrcAccessor> src,
975 SrcValue edge_marker)
976 }
977 \endcode
978 \deprecatedEnd
979
980 <b> Usage:</b>
981
982 <b>\#include</b> <vigra/edgedetection.hxx><br>
983 Namespace: vigra
984
985 \code
986 MultiArray<2, unsigned char> src(w,h), edges(2*w-1, 2*h-1);
987 ...
988
989 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
990 differenceOfExponentialCrackEdgeImage(src, edges,
991 0.8, 4.0, 1);
992
993 // close gaps, mark with 1
994 closeGapsInCrackEdgeImage(edges, 1);
995
996 // zero edges shorter than 20 pixels
997 removeShortEdges(edges, 10, 0);
998 \endcode
999
1000 \deprecatedUsage{closeGapsInCrackEdgeImage}
1001 \code
1002 vigra::BImage src(w,h), edges(2*w-1, 2*h-1);
1003
1004 // empty edge image
1005 edges = 0;
1006 ...
1007
1008 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
1009 vigra::differenceOfExponentialCrackEdgeImage(srcImageRange(src), destImage(edges),
1010 0.8, 4.0, 1);
1011
1012 // close gaps, mark with 1
1013 vigra::closeGapsInCrackEdgeImage(srcImageRange(edges), 1);
1014
1015 // zero edges shorter than 20 pixels
1016 vigra::removeShortEdges(srcImageRange(edges), 10, 0);
1017 \endcode
1018 <b> Required Interface:</b>
1019 \code
1020 SrcImageIterator src_upperleft, src_lowerright;
1021
1022 SrcAccessor src_accessor;
1023 DestAccessor dest_accessor;
1024
1025 SrcAccessor::value_type u = src_accessor(src_upperleft);
1026
1027 u == u
1028 u != u
1029
1030 SrcValue edge_marker;
1031 src_accessor.set(edge_marker, src_upperleft);
1032 \endcode
1033 \deprecatedEnd
1034 */
1035 doxygen_overloaded_function(template <...> void closeGapsInCrackEdgeImage)
1036
1037 template <class SrcIterator, class SrcAccessor, class SrcValue>
1038 void closeGapsInCrackEdgeImage(
1039 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
1040 SrcValue edge_marker)
1041 {
1042 int w = slr.x - sul.x;
1043 int h = slr.y - sul.y;
1044
1045 vigra_precondition(w % 2 == 1 && h % 2 == 1,
1046 "closeGapsInCrackEdgeImage(): Input is not a crack edge image (must have odd-numbered shape).");
1047
1048 int w2 = w / 2, h2 = h / 2, x, y;
1049
1050 int count1, count2, count3;
1051
1052 const Diff2D right(1,0);
1053 const Diff2D bottom(0,1);
1054 const Diff2D left(-1,0);
1055 const Diff2D top(0,-1);
1056
1057 const Diff2D leftdist[] = { Diff2D(0, 0), Diff2D(-1, 1), Diff2D(-2, 0), Diff2D(-1, -1)};
1058 const Diff2D rightdist[] = { Diff2D(2, 0), Diff2D(1, 1), Diff2D(0, 0), Diff2D(1, -1)};
1059 const Diff2D topdist[] = { Diff2D(1, -1), Diff2D(0, 0), Diff2D(-1, -1), Diff2D(0, -2)};
1060 const Diff2D bottomdist[] = { Diff2D(1, 1), Diff2D(0, 2), Diff2D(-1, 1), Diff2D(0, 0)};
1061
1062 int i;
1063
1064 SrcIterator sy = sul + Diff2D(0,1);
1065 SrcIterator sx;
1066
1067 // close 1-pixel wide gaps (x-direction)
1068 for(y=0; y<h2; ++y, sy.y+=2)
1069 {
1070 sx = sy + Diff2D(2,0);
1071
1072 for(x=2; x<w2; ++x, sx.x+=2)
1073 {
1074 if(sa(sx) == edge_marker) continue;
1075
1076 if(sa(sx, left) != edge_marker) continue;
1077 if(sa(sx, right) != edge_marker) continue;
1078
1079 count1 = 0;
1080 count2 = 0;
1081 count3 = 0;
1082
1083 for(i=0; i<4; ++i)
1084 {
1085 if(sa(sx, leftdist[i]) == edge_marker)
1086 {
1087 ++count1;
1088 count3 ^= 1 << i;
1089 }
1090 if(sa(sx, rightdist[i]) == edge_marker)
1091 {
1092 ++count2;
1093 count3 ^= 1 << i;
1094 }
1095 }
1096
1097 if(count1 <= 1 || count2 <= 1 || count3 == 15)
1098 {
1099 sa.set(edge_marker, sx);
1100 }
1101 }
1102 }
1103
1104 sy = sul + Diff2D(1,2);
1105
1106 // close 1-pixel wide gaps (y-direction)
1107 for(y=2; y<h2; ++y, sy.y+=2)
1108 {
1109 sx = sy;
1110
1111 for(x=0; x<w2; ++x, sx.x+=2)
1112 {
1113 if(sa(sx) == edge_marker) continue;
1114
1115 if(sa(sx, top) != edge_marker) continue;
1116 if(sa(sx, bottom) != edge_marker) continue;
1117
1118 count1 = 0;
1119 count2 = 0;
1120 count3 = 0;
1121
1122 for(i=0; i<4; ++i)
1123 {
1124 if(sa(sx, topdist[i]) == edge_marker)
1125 {
1126 ++count1;
1127 count3 ^= 1 << i;
1128 }
1129 if(sa(sx, bottomdist[i]) == edge_marker)
1130 {
1131 ++count2;
1132 count3 ^= 1 << i;
1133 }
1134 }
1135
1136 if(count1 <= 1 || count2 <= 1 || count3 == 15)
1137 {
1138 sa.set(edge_marker, sx);
1139 }
1140 }
1141 }
1142 }
1143
1144 template <class SrcIterator, class SrcAccessor, class SrcValue>
1145 inline void
1146 closeGapsInCrackEdgeImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1147 SrcValue edge_marker)
1148 {
1149 closeGapsInCrackEdgeImage(src.first, src.second, src.third,
1150 edge_marker);
1151 }
1152
1153 template <class T, class S, class Value>
1154 inline void
1155 closeGapsInCrackEdgeImage(MultiArrayView<2, T, S> image, Value edge_marker)
1156 {
1157 closeGapsInCrackEdgeImage(destImageRange(image), edge_marker);
1158 }
1159
1160 /********************************************************/
1161 /* */
1162 /* beautifyCrackEdgeImage */
1163 /* */
1164 /********************************************************/
1165
1166 /** \brief Beautify crack edge image for visualization.
1167
1168 This algorithm is applied as a post-processing operation of
1169 \ref differenceOfExponentialCrackEdgeImage(). The source image must fulfill
1170 the requirements of a \ref CrackEdgeImage, but will <b> not</b> do so after
1171 application of this algorithm. In particular, the algorithm removes zero-cells
1172 marked as edges to avoid staircase effects on diagonal lines like this:
1173
1174 \code
1175 original edge points (*) resulting edge points
1176
1177 . * . . . . * . . .
1178 . * * * . . . * . .
1179 . . . * . => . . . * .
1180 . . . * * . . . . *
1181 . . . . . . . . . .
1182 \endcode
1183
1184 Therefore, this algorithm should only be applied as a visualization aid, i.e.
1185 for human inspection. The algorithm assumes that edges are marked with <TT>edge_marker</TT>,
1186 and background pixels with <TT>background_marker</TT>. The image's value type must be
1187 equality comparable.
1188
1189 Note that this algorithm, unlike most other algorithms in VIGRA, operates in-place,
1190 i.e. on only one image.
1191
1192 <b> Declarations:</b>
1193
1194 pass 2D array views:
1195 \code
1196 namespace vigra {
1197 template <class T, class S, class Value>
1198 void
1199 beautifyCrackEdgeImage(MultiArrayView<2, T, S> image,
1200 Value edge_marker, Value background_marker);
1201 }
1202 \endcode
1203
1204 \deprecatedAPI{beautifyCrackEdgeImage}
1205 pass \ref ImageIterators and \ref DataAccessors :
1206 \code
1207 namespace vigra {
1208 template <class SrcIterator, class SrcAccessor, class SrcValue>
1209 void beautifyCrackEdgeImage(
1210 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
1211 SrcValue edge_marker, SrcValue background_marker)
1212 }
1213 \endcode
1214 use argument objects in conjunction with \ref ArgumentObjectFactories :
1215 \code
1216 namespace vigra {
1217 template <class SrcIterator, class SrcAccessor, class SrcValue>
1218 void beautifyCrackEdgeImage(
1219 triple<SrcIterator, SrcIterator, SrcAccessor> src,
1220 SrcValue edge_marker, SrcValue background_marker)
1221 }
1222 \endcode
1223 \deprecatedEnd
1224
1225 <b> Usage:</b>
1226
1227 <b>\#include</b> <vigra/edgedetection.hxx><br>
1228 Namespace: vigra
1229
1230 \code
1231 MultiArray<2, unsigned char> src(w,h), edges(2*w-1, 2*h-1);
1232 ...
1233
1234 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
1235 differenceOfExponentialCrackEdgeImage(src, edges,
1236 0.8, 4.0, 1);
1237
1238 // beautify edge image for visualization
1239 beautifyCrackEdgeImage(edges, 1, 0);
1240
1241 // show to the user ('window' is an unspecified GUI widget to display VIGRA images)
1242 window.open(edges);
1243 \endcode
1244
1245 \deprecatedUsage{beautifyCrackEdgeImage}
1246 \code
1247 vigra::BImage src(w,h), edges(2*w-1, 2*h-1);
1248
1249 // empty edge image
1250 edges = 0;
1251 ...
1252
1253 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
1254 vigra::differenceOfExponentialCrackEdgeImage(srcImageRange(src), destImage(edges),
1255 0.8, 4.0, 1);
1256
1257 // beautify edge image for visualization
1258 vigra::beautifyCrackEdgeImage(destImageRange(edges), 1, 0);
1259
1260 // show to the user
1261 window.open(edges);
1262 \endcode
1263 <b> Required Interface:</b>
1264 \code
1265 SrcImageIterator src_upperleft, src_lowerright;
1266
1267 SrcAccessor src_accessor;
1268 DestAccessor dest_accessor;
1269
1270 SrcAccessor::value_type u = src_accessor(src_upperleft);
1271
1272 u == u
1273 u != u
1274
1275 SrcValue background_marker;
1276 src_accessor.set(background_marker, src_upperleft);
1277 \endcode
1278 \deprecatedEnd
1279 */
1280 doxygen_overloaded_function(template <...> void beautifyCrackEdgeImage)
1281
1282 template <class SrcIterator, class SrcAccessor, class SrcValue>
1283 void beautifyCrackEdgeImage(
1284 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
1285 SrcValue edge_marker, SrcValue background_marker)
1286 {
1287 int w = slr.x - sul.x;
1288 int h = slr.y - sul.y;
1289
1290 vigra_precondition(w % 2 == 1 && h % 2 == 1,
1291 "beautifyCrackEdgeImage(): Input is not a crack edge image (must have odd-numbered shape).");
1292
1293 int w2 = w / 2, h2 = h / 2, x, y;
1294
1295 SrcIterator sy = sul + Diff2D(1,1);
1296 SrcIterator sx;
1297
1298 const Diff2D right(1,0);
1299 const Diff2D bottom(0,1);
1300 const Diff2D left(-1,0);
1301 const Diff2D top(0,-1);
1302
1303 // delete 0-cells at corners
1304 for(y=0; y<h2; ++y, sy.y+=2)
1305 {
1306 sx = sy;
1307
1308 for(x=0; x<w2; ++x, sx.x+=2)
1309 {
1310 if(sa(sx) != edge_marker) continue;
1311
1312 if(sa(sx, right) == edge_marker && sa(sx, left) == edge_marker) continue;
1313 if(sa(sx, bottom) == edge_marker && sa(sx, top) == edge_marker) continue;
1314
1315 sa.set(background_marker, sx);
1316 }
1317 }
1318 }
1319
1320 template <class SrcIterator, class SrcAccessor, class SrcValue>
1321 inline void
1322 beautifyCrackEdgeImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1323 SrcValue edge_marker, SrcValue background_marker)
1324 {
1325 beautifyCrackEdgeImage(src.first, src.second, src.third,
1326 edge_marker, background_marker);
1327 }
1328
1329 template <class T, class S, class Value>
1330 inline void
1331 beautifyCrackEdgeImage(MultiArrayView<2, T, S> image,
1332 Value edge_marker, Value background_marker)
1333 {
1334 beautifyCrackEdgeImage(destImageRange(image),
1335 edge_marker, background_marker);
1336 }
1337
1338
1339 /** Helper class that stores edgel attributes.
1340 */
1341 class Edgel
1342 {
1343 public:
1344
1345 /** The type of an Edgel's members.
1346 */
1347 typedef float value_type;
1348
1349 /** The edgel's sub-pixel x coordinate.
1350 */
1351 value_type x;
1352
1353 /** The edgel's sub-pixel y coordinate.
1354 */
1355 value_type y;
1356
1357 /** The edgel's strength (magnitude of the gradient vector).
1358 */
1359 value_type strength;
1360
1361 /** \brief The edgel's orientation.
1362
1363 This is the clockwise angle in radians
1364 between the x-axis and the edge, so that the bright side of the
1365 edge is on the left when one looks along the orientation vector.
1366 The angle is measured clockwise because the y-axis increases
1367 downwards (left-handed coordinate system):
1368
1369 \code
1370
1371 edgel axis
1372 \
1373 (dark \ (bright side)
1374 side) \
1375 \
1376 +------------> x-axis
1377 |\ |
1378 | \ /_/ orientation angle
1379 | \\
1380 | \
1381 |
1382 y-axis V
1383 \endcode
1384
1385 So, for example a vertical edge with its dark side on the left
1386 has orientation PI/2, and a horizontal edge with dark side on top
1387 has orientation PI. Obviously, the edge's orientation changes
1388 by PI if the contrast is reversed.
1389
1390 Note that this convention changed as of VIGRA version 1.7.0.
1391
1392 */
1393 value_type orientation;
1394
1395 Edgel()
1396 : x(0.0), y(0.0), strength(0.0), orientation(0.0)
1397 {}
1398
1399 Edgel(value_type ix, value_type iy, value_type is, value_type io)
1400 : x(ix), y(iy), strength(is), orientation(io)
1401 {}
1402 };
1403
1404 template <class SrcIterator, class SrcAccessor,
1405 class MagnitudeImage, class BackInsertable, class GradValue>
1406 void internalCannyFindEdgels(SrcIterator ul, SrcAccessor grad,
1407 MagnitudeImage const & magnitude,
1408 BackInsertable & edgels, GradValue grad_thresh)
1409 {
1410 typedef typename SrcAccessor::value_type PixelType;
1411 typedef typename PixelType::value_type ValueType;
1412
1413 vigra_precondition(grad_thresh >= NumericTraits<GradValue>::zero(),
1414 "cannyFindEdgels(): gradient threshold must not be negative.");
1415
1416 double t = 0.5 / VIGRA_CSTD::sin(M_PI/8.0);
1417
1418 ul += Diff2D(1,1);
1419 for(int y=1; y<magnitude.height()-1; ++y, ++ul.y)
1420 {
1421 SrcIterator ix = ul;
1422 for(int x=1; x<magnitude.width()-1; ++x, ++ix.x)
1423 {
1424 double mag = magnitude(x, y);
1425 if(mag <= grad_thresh)
1426 continue;
1427 ValueType gradx = grad.getComponent(ix, 0);
1428 ValueType grady = grad.getComponent(ix, 1);
1429
1430 int dx = (int)VIGRA_CSTD::floor(gradx*t/mag + 0.5);
1431 int dy = (int)VIGRA_CSTD::floor(grady*t/mag + 0.5);
1432
1433 int x1 = x - dx,
1434 x2 = x + dx,
1435 y1 = y - dy,
1436 y2 = y + dy;
1437
1438 double m1 = magnitude(x1, y1);
1439 double m3 = magnitude(x2, y2);
1440
1441 if(m1 < mag && m3 <= mag)
1442 {
1443 Edgel edgel;
1444
1445 // local maximum => quadratic interpolation of sub-pixel location
1446 double del = 0.5 * (m1 - m3) / (m1 + m3 - 2.0*mag);
1447 edgel.x = Edgel::value_type(x + dx*del);
1448 edgel.y = Edgel::value_type(y + dy*del);
1449 edgel.strength = Edgel::value_type(mag);
1450 double orientation = VIGRA_CSTD::atan2(grady, gradx) + 0.5*M_PI;
1451 if(orientation < 0.0)
1452 orientation += 2.0*M_PI;
1453 edgel.orientation = Edgel::value_type(orientation);
1454 edgels.push_back(edgel);
1455 }
1456 }
1457 }
1458 }
1459
1460 /********************************************************/
1461 /* */
1462 /* cannyEdgelList */
1463 /* */
1464 /********************************************************/
1465
1466 /** \brief Simple implementation of Canny's edge detector.
1467
1468 The function can be called in two modes: If you pass a 'scale', it is assumed that the
1469 original image is scalar, and the Gaussian gradient is internally computed at the
1470 given 'scale'. If the function is called without scale parameter, it is assumed that
1471 the given image already contains the gradient (i.e. its value_type must be
1472 a vector of length 2).
1473
1474 On the basis of the gradient image, a simple non-maxima suppression is performed:
1475 for each 3x3 neighborhood, it is determined whether the center pixel has
1476 larger gradient magnitude than its two neighbors in gradient direction
1477 (where the direction is rounded into octants). If this is the case,
1478 a new \ref Edgel is appended to the given vector of <TT>edgels</TT>. The subpixel
1479 edgel position is determined by fitting a parabola to the three gradient
1480 magnitude values mentioned above. The sub-pixel location of the parabola's tip
1481 and the gradient magnitude and direction (from the pixel center)
1482 are written in the newly created edgel.
1483
1484 <b> Declarations:</b>
1485
1486 pass 2D array views:
1487 \code
1488 namespace vigra {
1489 // compute edgels from a scalar image (determine gradient internally at 'scale')
1490 template <class T, class S, class BackInsertable>
1491 void
1492 cannyEdgelList(MultiArrayView<2, T, S> const & src,
1493 BackInsertable & edgels,
1494 double scale);
1495
1496 // compute edgels from a pre-computed gradient image
1497 template <class T, class S, class BackInsertable>
1498 void
1499 cannyEdgelList(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
1500 BackInsertable & edgels);
1501 }
1502 \endcode
1503
1504 \deprecatedAPI{cannyEdgelList}
1505 pass \ref ImageIterators and \ref DataAccessors :
1506 \code
1507 namespace vigra {
1508 // compute edgels from a gradient image
1509 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1510 void
1511 cannyEdgelList(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1512 BackInsertable & edgels);
1513
1514 // compute edgels from a scalar image (determine gradient internally at 'scale')
1515 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1516 void
1517 cannyEdgelList(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1518 BackInsertable & edgels, double scale);
1519 }
1520 \endcode
1521 use argument objects in conjunction with \ref ArgumentObjectFactories :
1522 \code
1523 namespace vigra {
1524 // compute edgels from a gradient image
1525 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1526 void
1527 cannyEdgelList(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1528 BackInsertable & edgels);
1529
1530 // compute edgels from a scalar image (determine gradient internally at 'scale')
1531 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1532 void
1533 cannyEdgelList(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1534 BackInsertable & edgels, double scale);
1535 }
1536 \endcode
1537 \deprecatedEnd
1538
1539 <b> Usage:</b>
1540
1541 <b>\#include</b> <vigra/edgedetection.hxx><br>
1542 Namespace: vigra
1543
1544 \code
1545 MultiArray<2, unsigned char> src(w,h);
1546
1547 // create empty edgel list
1548 std::vector<vigra::Edgel> edgels;
1549 ...
1550
1551 // find edgels at scale 0.8
1552 cannyEdgelList(src, edgels, 0.8);
1553 \endcode
1554
1555 \deprecatedUsage{cannyEdgelList}
1556 \code
1557 vigra::BImage src(w,h);
1558
1559 // empty edgel list
1560 std::vector<vigra::Edgel> edgels;
1561 ...
1562
1563 // find edgels at scale 0.8
1564 vigra::cannyEdgelList(srcImageRange(src), edgels, 0.8);
1565 \endcode
1566 <b> Required Interface:</b>
1567 \code
1568 SrcImageIterator src_upperleft;
1569 SrcAccessor src_accessor;
1570
1571 src_accessor(src_upperleft);
1572
1573 BackInsertable edgels;
1574 edgels.push_back(Edgel());
1575 \endcode
1576 SrcAccessor::value_type must be a type convertible to float
1577 \deprecatedEnd
1578
1579 <b> Preconditions:</b>
1580
1581 \code
1582 scale > 0
1583 \endcode
1584 */
1585 doxygen_overloaded_function(template <...> void cannyEdgelList)
1586
1587 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1588 void
1589 cannyEdgelList(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1590 BackInsertable & edgels, double scale)
1591 {
1592 typedef typename NumericTraits<typename SrcAccessor::value_type>::RealPromote TmpType;
1593 BasicImage<TinyVector<TmpType, 2> > grad(lr-ul);
1594 gaussianGradient(srcIterRange(ul, lr, src), destImage(grad), scale);
1595
1596 cannyEdgelList(srcImageRange(grad), edgels);
1597 }
1598
1599 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1600 void
1601 cannyEdgelList(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1602 BackInsertable & edgels)
1603 {
1604 using namespace functor;
1605
1606 typedef typename SrcAccessor::value_type SrcType;
1607 typedef typename NumericTraits<typename SrcType::value_type>::RealPromote TmpType;
1608 BasicImage<TmpType> magnitude(lr-ul);
1609 transformImage(srcIterRange(ul, lr, src), destImage(magnitude), norm(Arg1()));
1610
1611 // find edgels
1612 internalCannyFindEdgels(ul, src, magnitude, edgels, NumericTraits<TmpType>::zero());
1613 }
1614
1615 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1616 inline void
1617 cannyEdgelList(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1618 BackInsertable & edgels, double scale)
1619 {
1620 cannyEdgelList(src.first, src.second, src.third, edgels, scale);
1621 }
1622
1623 template <class SrcIterator, class SrcAccessor, class BackInsertable>
1624 inline void
1625 cannyEdgelList(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1626 BackInsertable & edgels)
1627 {
1628 cannyEdgelList(src.first, src.second, src.third, edgels);
1629 }
1630
1631 template <class T, class S, class BackInsertable>
1632 inline void
1633 cannyEdgelList(MultiArrayView<2, T, S> const & src,
1634 BackInsertable & edgels, double scale)
1635 {
1636 cannyEdgelList(srcImageRange(src), edgels, scale);
1637 }
1638
1639 template <class T, class S, class BackInsertable>
1640 inline void
1641 cannyEdgelList(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
1642 BackInsertable & edgels)
1643 {
1644 cannyEdgelList(srcImageRange(src), edgels);
1645 }
1646
1647 /********************************************************/
1648 /* */
1649 /* cannyEdgelListThreshold */
1650 /* */
1651 /********************************************************/
1652
1653 /** \brief Canny's edge detector with thresholding.
1654
1655 This function works exactly like \ref cannyEdgelList(), but
1656 you also pass a threshold for the minimal gradient magnitude,
1657 so that edgels whose strength is below the threshold are not
1658 inserted into the edgel list.
1659
1660 <b> Declarations:</b>
1661
1662 pass 2D array views:
1663 \code
1664 namespace vigra {
1665 // compute edgels from a scalar image (determine gradient internally at 'scale')
1666 template <class T, class S,
1667 class BackInsertable, class GradValue>
1668 void
1669 cannyEdgelListThreshold(MultiArrayView<2, T, S> const & src,
1670 BackInsertable & edgels,
1671 double scale,
1672 GradValue grad_threshold);
1673
1674 // compute edgels from a pre-computed gradient image
1675 template <class T, class S,
1676 class BackInsertable, class GradValue>
1677 void
1678 cannyEdgelListThreshold(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
1679 BackInsertable & edgels,
1680 GradValue grad_threshold);
1681 }
1682 \endcode
1683
1684 \deprecatedAPI{cannyEdgelListThreshold}
1685 pass \ref ImageIterators and \ref DataAccessors :
1686 \code
1687 namespace vigra {
1688 // compute edgels from a gradient image
1689 template <class SrcIterator, class SrcAccessor,
1690 class BackInsertable, class GradValue>
1691 void
1692 cannyEdgelListThreshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1693 BackInsertable & edgels, GradValue grad_threshold);
1694
1695 // compute edgels from a scalar image (determine gradient internally at 'scale')
1696 template <class SrcIterator, class SrcAccessor,
1697 class BackInsertable, class GradValue>
1698 void
1699 cannyEdgelListThreshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1700 BackInsertable & edgels, double scale, GradValue grad_threshold);
1701 }
1702 \endcode
1703 use argument objects in conjunction with \ref ArgumentObjectFactories :
1704 \code
1705 namespace vigra {
1706 // compute edgels from a gradient image
1707 template <class SrcIterator, class SrcAccessor,
1708 class BackInsertable, class GradValue>
1709 void
1710 cannyEdgelListThreshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1711 BackInsertable & edgels, GradValue grad_threshold);
1712
1713 // compute edgels from a scalar image (determine gradient internally at 'scale')
1714 template <class SrcIterator, class SrcAccessor,
1715 class BackInsertable, class GradValue>
1716 void
1717 cannyEdgelListThreshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1718 BackInsertable & edgels, double scale, GradValue grad_threshold);
1719 }
1720 \endcode
1721 \deprecatedEnd
1722
1723 <b> Usage:</b>
1724
1725 <b>\#include</b> <vigra/edgedetection.hxx><br>
1726 Namespace: vigra
1727
1728 \code
1729 MultiArray<2, unsigned char> src(w,h);
1730
1731 // create empty edgel list
1732 std::vector<vigra::Edgel> edgels;
1733 ...
1734
1735 // find edgels at scale 0.8, only considering gradient magnitudes above 2.0
1736 cannyEdgelListThreshold(src, edgels, 0.8, 2.0);
1737 \endcode
1738
1739 \deprecatedUsage{cannyEdgelListThreshold}
1740 \code
1741 vigra::BImage src(w,h);
1742
1743 // empty edgel list
1744 std::vector<vigra::Edgel> edgels;
1745 ...
1746
1747 // find edgels at scale 0.8, only considering gradient above 2.0
1748 vigra::cannyEdgelListThreshold(srcImageRange(src), edgels, 0.8, 2.0);
1749 \endcode
1750 <b> Required Interface:</b>
1751 \code
1752 SrcImageIterator src_upperleft;
1753 SrcAccessor src_accessor;
1754
1755 src_accessor(src_upperleft);
1756
1757 BackInsertable edgels;
1758 edgels.push_back(Edgel());
1759 \endcode
1760 SrcAccessor::value_type must be a type convertible to float
1761 \deprecatedEnd
1762
1763 <b> Preconditions:</b>
1764
1765 \code
1766 scale > 0
1767 \endcode
1768 */
1769 doxygen_overloaded_function(template <...> void cannyEdgelListThreshold)
1770
1771 template <class SrcIterator, class SrcAccessor,
1772 class BackInsertable, class GradValue>
1773 void
1774 cannyEdgelListThreshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1775 BackInsertable & edgels, double scale, GradValue grad_threshold)
1776 {
1777 typedef typename NumericTraits<typename SrcAccessor::value_type>::RealPromote TmpType;
1778 BasicImage<TinyVector<TmpType, 2> > grad(lr-ul);
1779 gaussianGradient(srcIterRange(ul, lr, src), destImage(grad), scale);
1780
1781 cannyEdgelListThreshold(srcImageRange(grad), edgels, grad_threshold);
1782 }
1783
1784 template <class SrcIterator, class SrcAccessor,
1785 class BackInsertable, class GradValue>
1786 void
1787 cannyEdgelListThreshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
1788 BackInsertable & edgels, GradValue grad_threshold)
1789 {
1790 using namespace functor;
1791
1792 typedef typename SrcAccessor::value_type SrcType;
1793 typedef typename NumericTraits<typename SrcType::value_type>::RealPromote TmpType;
1794 BasicImage<TmpType> magnitude(lr-ul);
1795 transformImage(srcIterRange(ul, lr, src), destImage(magnitude), norm(Arg1()));
1796
1797 // find edgels
1798 internalCannyFindEdgels(ul, src, magnitude, edgels, grad_threshold);
1799 }
1800
1801 template <class SrcIterator, class SrcAccessor,
1802 class BackInsertable, class GradValue>
1803 inline void
1804 cannyEdgelListThreshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1805 BackInsertable & edgels, double scale, GradValue grad_threshold)
1806 {
1807 cannyEdgelListThreshold(src.first, src.second, src.third, edgels, scale, grad_threshold);
1808 }
1809
1810 template <class SrcIterator, class SrcAccessor,
1811 class BackInsertable, class GradValue>
1812 inline void
1813 cannyEdgelListThreshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1814 BackInsertable & edgels, GradValue grad_threshold)
1815 {
1816 cannyEdgelListThreshold(src.first, src.second, src.third, edgels, grad_threshold);
1817 }
1818
1819 template <class T, class S,
1820 class BackInsertable, class GradValue>
1821 inline void
1822 cannyEdgelListThreshold(MultiArrayView<2, T, S> const & src,
1823 BackInsertable & edgels,
1824 double scale,
1825 GradValue grad_threshold)
1826 {
1827 cannyEdgelListThreshold(srcImageRange(src), edgels, scale, grad_threshold);
1828 }
1829
1830 template <class T, class S,
1831 class BackInsertable, class GradValue>
1832 inline void
1833 cannyEdgelListThreshold(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
1834 BackInsertable & edgels,
1835 GradValue grad_threshold)
1836 {
1837 cannyEdgelListThreshold(srcImageRange(src), edgels, grad_threshold);
1838 }
1839
1840
1841 /********************************************************/
1842 /* */
1843 /* cannyEdgeImage */
1844 /* */
1845 /********************************************************/
1846
1847 /** \brief Detect and mark edges in an edge image using Canny's algorithm.
1848
1849 This operator first calls \ref cannyEdgelList() with the given scale to generate an
1850 edgel list for the given image. Then it scans this list and selects edgels
1851 whose strength is above the given <TT>gradient_threshold</TT>. For each of these
1852 edgels, the edgel's location is rounded to the nearest pixel, and that
1853 pixel marked with the given <TT>edge_marker</TT>.
1854
1855 <b> Declarations:</b>
1856
1857 pass 2D array views:
1858 \code
1859 namespace vigra {
1860 template <class T1, class S1,
1861 class T2, class S2,
1862 class GradValue, class DestValue>
1863 void
1864 cannyEdgeImage(MultiArrayView<2, T1, S1> const & src,
1865 MultiArrayView<2, T2, S2> dest,
1866 double scale,
1867 GradValue gradient_threshold,
1868 DestValue edge_marker);
1869 }
1870 \endcode
1871
1872 \deprecatedAPI{cannyEdgeImage}
1873 pass \ref ImageIterators and \ref DataAccessors :
1874 \code
1875 namespace vigra {
1876 template <class SrcIterator, class SrcAccessor,
1877 class DestIterator, class DestAccessor,
1878 class GradValue, class DestValue>
1879 void cannyEdgeImage(
1880 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
1881 DestIterator dul, DestAccessor da,
1882 double scale, GradValue gradient_threshold, DestValue edge_marker);
1883 }
1884 \endcode
1885 use argument objects in conjunction with \ref ArgumentObjectFactories :
1886 \code
1887 namespace vigra {
1888 template <class SrcIterator, class SrcAccessor,
1889 class DestIterator, class DestAccessor,
1890 class GradValue, class DestValue>
1891 void cannyEdgeImage(
1892 triple<SrcIterator, SrcIterator, SrcAccessor> src,
1893 pair<DestIterator, DestAccessor> dest,
1894 double scale, GradValue gradient_threshold, DestValue edge_marker);
1895 }
1896 \endcode
1897 \deprecatedEnd
1898
1899 <b> Usage:</b>
1900
1901 <b>\#include</b> <vigra/edgedetection.hxx><br>
1902 Namespace: vigra
1903
1904 \code
1905 MultiArray<2, unsigned char> src(w,h), edges(w,h);
1906 ...
1907
1908 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
1909 cannyEdgeImage(src, edges, 0.8, 4.0, 1);
1910 \endcode
1911
1912 \deprecatedUsage{cannyEdgeImage}
1913 \code
1914 vigra::BImage src(w,h), edges(w,h);
1915
1916 // empty edge image
1917 edges = 0;
1918 ...
1919
1920 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1
1921 vigra::cannyEdgeImage(srcImageRange(src), destImage(edges),
1922 0.8, 4.0, 1);
1923 \endcode
1924 <b> Required Interface:</b>
1925 see also: \ref cannyEdgelList().
1926 \code
1927 DestImageIterator dest_upperleft;
1928 DestAccessor dest_accessor;
1929 DestValue edge_marker;
1930
1931 dest_accessor.set(edge_marker, dest_upperleft, vigra::Diff2D(1,1));
1932 \endcode
1933 \deprecatedEnd
1934
1935 <b> Preconditions:</b>
1936
1937 \code
1938 scale > 0
1939 gradient_threshold > 0
1940 \endcode
1941 */
1942 doxygen_overloaded_function(template <...> void cannyEdgeImage)
1943
1944 template <class SrcIterator, class SrcAccessor,
1945 class DestIterator, class DestAccessor,
1946 class GradValue, class DestValue>
1947 void cannyEdgeImage(
1948 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
1949 DestIterator dul, DestAccessor da,
1950 double scale, GradValue gradient_threshold, DestValue edge_marker)
1951 {
1952 std::vector<Edgel> edgels;
1953
1954 cannyEdgelListThreshold(sul, slr, sa, edgels, scale, gradient_threshold);
1955
1956 int w = slr.x - sul.x;
1957 int h = slr.y - sul.y;
1958
1959 for(unsigned int i=0; i<edgels.size(); ++i)
1960 {
1961 Diff2D pix((int)(edgels[i].x + 0.5), (int)(edgels[i].y + 0.5));
1962
1963 if(pix.x < 0 || pix.x >= w || pix.y < 0 || pix.y >= h)
1964 continue;
1965
1966 da.set(edge_marker, dul, pix);
1967 }
1968 }
1969
1970 template <class SrcIterator, class SrcAccessor,
1971 class DestIterator, class DestAccessor,
1972 class GradValue, class DestValue>
1973 inline void
1974 cannyEdgeImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
1975 pair<DestIterator, DestAccessor> dest,
1976 double scale, GradValue gradient_threshold, DestValue edge_marker)
1977 {
1978 cannyEdgeImage(src.first, src.second, src.third,
1979 dest.first, dest.second,
1980 scale, gradient_threshold, edge_marker);
1981 }
1982
1983 template <class T1, class S1,
1984 class T2, class S2,
1985 class GradValue, class DestValue>
1986 inline void
1987 cannyEdgeImage(MultiArrayView<2, T1, S1> const & src,
1988 MultiArrayView<2, T2, S2> dest,
1989 double scale, GradValue gradient_threshold, DestValue edge_marker)
1990 {
1991 vigra_precondition(src.shape() == dest.shape(),
1992 "cannyEdgeImage(): shape mismatch between input and output.");
1993 cannyEdgeImage(srcImageRange(src),
1994 destImage(dest),
1995 scale, gradient_threshold, edge_marker);
1996 }
1997
1998 /********************************************************/
1999
2000 namespace detail {
2001
2002 template <class DestIterator>
2003 int neighborhoodConfiguration(DestIterator dul)
2004 {
2005 int v = 0;
2006 NeighborhoodCirculator<DestIterator, EightNeighborCode> c(dul, EightNeighborCode::SouthEast);
2007 for(int i=0; i<8; ++i, --c)
2008 {
2009 v = (v << 1) | ((*c != 0) ? 1 : 0);
2010 }
2011
2012 return v;
2013 }
2014
2015 template <class GradValue>
2016 struct SimplePoint
2017 {
2018 Diff2D point;
2019 GradValue grad;
2020
2021 SimplePoint(Diff2D const & p, GradValue g)
2022 : point(p), grad(g)
2023 {}
2024
2025 bool operator<(SimplePoint const & o) const
2026 {
2027 return grad < o.grad;
2028 }
2029
2030 bool operator>(SimplePoint const & o) const
2031 {
2032 return grad > o.grad;
2033 }
2034 };
2035
2036 template <class SrcIterator, class SrcAccessor,
2037 class DestIterator, class DestAccessor,
2038 class GradValue, class DestValue>
2039 void cannyEdgeImageFromGrad(
2040 SrcIterator sul, SrcIterator slr, SrcAccessor grad,
2041 DestIterator dul, DestAccessor da,
2042 GradValue gradient_threshold, DestValue edge_marker)
2043 {
2044 typedef typename SrcAccessor::value_type PixelType;
2045 typedef typename NormTraits<PixelType>::SquaredNormType NormType;
2046
2047 NormType zero = NumericTraits<NormType>::zero();
2048 double tan22_5 = M_SQRT2 - 1.0;
2049 typename NormTraits<GradValue>::SquaredNormType g2thresh = squaredNorm(gradient_threshold);
2050
2051 int w = slr.x - sul.x;
2052 int h = slr.y - sul.y;
2053
2054 sul += Diff2D(1,1);
2055 dul += Diff2D(1,1);
2056 Diff2D p(0,0);
2057
2058 for(int y = 1; y < h-1; ++y, ++sul.y, ++dul.y)
2059 {
2060 SrcIterator sx = sul;
2061 DestIterator dx = dul;
2062 for(int x = 1; x < w-1; ++x, ++sx.x, ++dx.x)
2063 {
2064 PixelType g = grad(sx);
2065 NormType g2n = squaredNorm(g);
2066 if(g2n < g2thresh)
2067 continue;
2068
2069 NormType g2n1, g2n3;
2070 // find out quadrant
2071 if(abs(g[1]) < tan22_5*abs(g[0]))
2072 {
2073 // north-south edge
2074 g2n1 = squaredNorm(grad(sx, Diff2D(-1, 0)));
2075 g2n3 = squaredNorm(grad(sx, Diff2D(1, 0)));
2076 }
2077 else if(abs(g[0]) < tan22_5*abs(g[1]))
2078 {
2079 // west-east edge
2080 g2n1 = squaredNorm(grad(sx, Diff2D(0, -1)));
2081 g2n3 = squaredNorm(grad(sx, Diff2D(0, 1)));
2082 }
2083 else if(g[0]*g[1] < zero)
2084 {
2085 // north-west-south-east edge
2086 g2n1 = squaredNorm(grad(sx, Diff2D(1, -1)));
2087 g2n3 = squaredNorm(grad(sx, Diff2D(-1, 1)));
2088 }
2089 else
2090 {
2091 // north-east-south-west edge
2092 g2n1 = squaredNorm(grad(sx, Diff2D(-1, -1)));
2093 g2n3 = squaredNorm(grad(sx, Diff2D(1, 1)));
2094 }
2095
2096 if(g2n1 < g2n && g2n3 <= g2n)
2097 {
2098 da.set(edge_marker, dx);
2099 }
2100 }
2101 }
2102 }
2103
2104 } // namespace detail
2105
2106 /********************************************************/
2107 /* */
2108 /* cannyEdgeImageFromGradWithThinning */
2109 /* */
2110 /********************************************************/
2111
2112 /** \brief Detect and mark edges in an edge image using Canny's algorithm.
2113
2114 The input pixels of this algorithm must be vectors of length 2 (see Required Interface below).
2115 It first searches for all pixels whose gradient magnitude is larger
2116 than the given <tt>gradient_threshold</tt> and larger than the magnitude of its two neighbors
2117 in gradient direction (where these neighbors are determined by nearest neighbor
2118 interpolation, i.e. according to the octant where the gradient points into).
2119 The resulting edge pixel candidates are then subjected to topological thinning
2120 so that the remaining edge pixels can be linked into edgel chains with a provable,
2121 non-heuristic algorithm. Thinning is performed so that the pixels with highest gradient
2122 magnitude survive. Optionally, the outermost pixels are marked as edge pixels
2123 as well when <tt>addBorder</tt> is true. The remaining pixels will be marked in the destination
2124 image with the value of <tt>edge_marker</tt> (all non-edge pixels remain untouched).
2125
2126 <b> Declarations:</b>
2127
2128 pass 2D array views:
2129 \code
2130 namespace vigra {
2131 template <class T1, class S1,
2132 class T2, class S2,
2133 class GradValue, class DestValue>
2134 void
2135 cannyEdgeImageFromGradWithThinning(MultiArrayView<2, TinyVector<T1, 2>, S1> const & src,
2136 MultiArrayView<2, T2, S2> dest,
2137 GradValue gradient_threshold,
2138 DestValue edge_marker,
2139 bool addBorder = true);
2140 }
2141 \endcode
2142
2143 \deprecatedAPI{cannyEdgeImageFromGradWithThinning}
2144 pass \ref ImageIterators and \ref DataAccessors :
2145 \code
2146 namespace vigra {
2147 template <class SrcIterator, class SrcAccessor,
2148 class DestIterator, class DestAccessor,
2149 class GradValue, class DestValue>
2150 void cannyEdgeImageFromGradWithThinning(
2151 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
2152 DestIterator dul, DestAccessor da,
2153 GradValue gradient_threshold,
2154 DestValue edge_marker, bool addBorder = true);
2155 }
2156 \endcode
2157 use argument objects in conjunction with \ref ArgumentObjectFactories :
2158 \code
2159 namespace vigra {
2160 template <class SrcIterator, class SrcAccessor,
2161 class DestIterator, class DestAccessor,
2162 class GradValue, class DestValue>
2163 void cannyEdgeImageFromGradWithThinning(
2164 triple<SrcIterator, SrcIterator, SrcAccessor> src,
2165 pair<DestIterator, DestAccessor> dest,
2166 GradValue gradient_threshold,
2167 DestValue edge_marker, bool addBorder = true);
2168 }
2169 \endcode
2170 \deprecatedEnd
2171
2172 <b> Usage:</b>
2173
2174 <b>\#include</b> <vigra/edgedetection.hxx><br>
2175 Namespace: vigra
2176
2177 \code
2178 MultiArray<2, unsigned char> src(w,h), edges(w,h);
2179
2180 MultiArray<2, TinyVector<float, 2> > grad(w,h);
2181 // compute the image gradient at scale 0.8
2182 gaussianGradient(src, grad, 0.8);
2183
2184 // find edges with gradient larger than 4.0, mark with 1, and add border
2185 cannyEdgeImageFromGradWithThinning(grad, edges, 4.0, 1, true);
2186 \endcode
2187
2188 \deprecatedUsage{cannyEdgeImageFromGradWithThinning}
2189 \code
2190 vigra::BImage src(w,h), edges(w,h);
2191
2192 vigra::FVector2Image grad(w,h);
2193 // compute the image gradient at scale 0.8
2194 vigra::gaussianGradient(srcImageRange(src), destImage(grad), 0.8);
2195
2196 // empty edge image
2197 edges = 0;
2198 // find edges gradient larger than 4.0, mark with 1, and add border
2199 vigra::cannyEdgeImageFromGradWithThinning(srcImageRange(grad), destImage(edges),
2200 4.0, 1, true);
2201 \endcode
2202 <b> Required Interface:</b>
2203 \code
2204 // the input pixel type must be a vector with two elements
2205 SrcImageIterator src_upperleft;
2206 SrcAccessor src_accessor;
2207 typedef SrcAccessor::value_type SrcPixel;
2208 typedef NormTraits<SrcPixel>::SquaredNormType SrcSquaredNormType;
2209
2210 SrcPixel g = src_accessor(src_upperleft);
2211 SrcPixel::value_type g0 = g[0];
2212 SrcSquaredNormType gn = squaredNorm(g);
2213
2214 DestImageIterator dest_upperleft;
2215 DestAccessor dest_accessor;
2216 DestValue edge_marker;
2217
2218 dest_accessor.set(edge_marker, dest_upperleft, vigra::Diff2D(1,1));
2219 \endcode
2220 \deprecatedEnd
2221
2222 <b> Preconditions:</b>
2223
2224 \code
2225 gradient_threshold > 0
2226 \endcode
2227 */
2228 doxygen_overloaded_function(template <...> void cannyEdgeImageFromGradWithThinning)
2229
2230 template <class SrcIterator, class SrcAccessor,
2231 class DestIterator, class DestAccessor,
2232 class GradValue, class DestValue>
2233 void cannyEdgeImageFromGradWithThinning(
2234 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
2235 DestIterator dul, DestAccessor da,
2236 GradValue gradient_threshold,
2237 DestValue edge_marker, bool addBorder = true)
2238 {
2239 int w = slr.x - sul.x;
2240 int h = slr.y - sul.y;
2241
2242 BImage edgeImage(w, h, BImage::value_type(0));
2243 BImage::traverser eul = edgeImage.upperLeft();
2244 BImage::Accessor ea = edgeImage.accessor();
2245 if(addBorder)
2246 initImageBorder(destImageRange(edgeImage), 1, 1);
2247 detail::cannyEdgeImageFromGrad(sul, slr, sa, eul, ea, gradient_threshold, 1);
2248
2249 bool isSimplePoint[256] = {
2250 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,
2251 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
2252 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,
2253 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1,
2254 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1,
2255 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0,
2256 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0,
2257 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1,
2258 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
2259 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
2260 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1,
2261 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0,
2262 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0,
2263 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1,
2264 1, 0, 1, 0 };
2265
2266 eul += Diff2D(1,1);
2267 sul += Diff2D(1,1);
2268 int w2 = w-2;
2269 int h2 = h-2;
2270
2271 typedef detail::SimplePoint<GradValue> SP;
2272 // use std::greater because we need the smallest gradients at the top of the queue
2273 std::priority_queue<SP, std::vector<SP>, std::greater<SP> > pqueue;
2274
2275 Diff2D p(0,0);
2276 for(; p.y < h2; ++p.y)
2277 {
2278 for(p.x = 0; p.x < w2; ++p.x)
2279 {
2280 BImage::traverser e = eul + p;
2281 if(*e == 0)
2282 continue;
2283 int v = detail::neighborhoodConfiguration(e);
2284 if(isSimplePoint[v])
2285 {
2286 pqueue.push(SP(p, norm(sa(sul+p))));
2287 *e = 2; // remember that it is already in queue
2288 }
2289 }
2290 }
2291
2292 const Diff2D dist[] = { Diff2D(-1,0), Diff2D(0,-1), Diff2D(1,0), Diff2D(0,1) };
2293
2294 while(pqueue.size())
2295 {
2296 p = pqueue.top().point;
2297 pqueue.pop();
2298
2299 BImage::traverser e = eul + p;
2300 int v = detail::neighborhoodConfiguration(e);
2301 if(!isSimplePoint[v])
2302 continue; // point may no longer be simple because its neighbors changed
2303
2304 *e = 0; // delete simple point
2305
2306 for(int i=0; i<4; ++i)
2307 {
2308 Diff2D pneu = p + dist[i];
2309 if(pneu.x == -1 || pneu.y == -1 || pneu.x == w2 || pneu.y == h2)
2310 continue; // do not remove points at the border
2311
2312 BImage::traverser eneu = eul + pneu;
2313 if(*eneu == 1) // point is boundary and not yet in the queue
2314 {
2315 int v = detail::neighborhoodConfiguration(eneu);
2316 if(isSimplePoint[v])
2317 {
2318 pqueue.push(SP(pneu, norm(sa(sul+pneu))));
2319 *eneu = 2; // remember that it is already in queue
2320 }
2321 }
2322 }
2323 }
2324
2325 initImageIf(destIterRange(dul, dul+Diff2D(w,h), da),
2326 maskImage(edgeImage), edge_marker);
2327 }
2328
2329 template <class SrcIterator, class SrcAccessor,
2330 class DestIterator, class DestAccessor,
2331 class GradValue, class DestValue>
2332 inline void cannyEdgeImageFromGradWithThinning(
2333 triple<SrcIterator, SrcIterator, SrcAccessor> src,
2334 pair<DestIterator, DestAccessor> dest,
2335 GradValue gradient_threshold,
2336 DestValue edge_marker, bool addBorder = true)
2337 {
2338 cannyEdgeImageFromGradWithThinning(src.first, src.second, src.third,
2339 dest.first, dest.second,
2340 gradient_threshold, edge_marker, addBorder);
2341 }
2342
2343 template <class T1, class S1,
2344 class T2, class S2,
2345 class GradValue, class DestValue>
2346 inline void
2347 cannyEdgeImageFromGradWithThinning(MultiArrayView<2, TinyVector<T1, 2>, S1> const & src,
2348 MultiArrayView<2, T2, S2> dest,
2349 GradValue gradient_threshold,
2350 DestValue edge_marker, bool addBorder = true)
2351 {
2352 vigra_precondition(src.shape() == dest.shape(),
2353 "cannyEdgeImageFromGradWithThinning(): shape mismatch between input and output.");
2354 cannyEdgeImageFromGradWithThinning(srcImageRange(src),
2355 destImage(dest),
2356 gradient_threshold, edge_marker, addBorder);
2357 }
2358
2359 /********************************************************/
2360 /* */
2361 /* cannyEdgeImageWithThinning */
2362 /* */
2363 /********************************************************/
2364
2365 /** \brief Detect and mark edges in an edge image using Canny's algorithm.
2366
2367 This operator first calls \ref gaussianGradient() to compute the gradient of the input
2368 image, ad then \ref cannyEdgeImageFromGradWithThinning() to generate an
2369 edge image. See there for more detailed documentation.
2370
2371 <b> Declarations:</b>
2372
2373 pass 2D array views:
2374 \code
2375 namespace vigra {
2376 template <class T1, class S1,
2377 class T2, class S2,
2378 class GradValue, class DestValue>
2379 void
2380 cannyEdgeImageWithThinning(MultiArrayView<2, T1, S1> const & src,
2381 MultiArrayView<2, T2, S2> dest,
2382 double scale,
2383 GradValue gradient_threshold,
2384 DestValue edge_marker,
2385 bool addBorder = true);
2386 }
2387 \endcode
2388
2389 \deprecatedAPI{cannyEdgeImageWithThinning}
2390 pass \ref ImageIterators and \ref DataAccessors :
2391 \code
2392 namespace vigra {
2393 template <class SrcIterator, class SrcAccessor,
2394 class DestIterator, class DestAccessor,
2395 class GradValue, class DestValue>
2396 void cannyEdgeImageWithThinning(
2397 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
2398 DestIterator dul, DestAccessor da,
2399 double scale, GradValue gradient_threshold,
2400 DestValue edge_marker, bool addBorder = true);
2401 }
2402 \endcode
2403 use argument objects in conjunction with \ref ArgumentObjectFactories :
2404 \code
2405 namespace vigra {
2406 template <class SrcIterator, class SrcAccessor,
2407 class DestIterator, class DestAccessor,
2408 class GradValue, class DestValue>
2409 void cannyEdgeImageWithThinning(
2410 triple<SrcIterator, SrcIterator, SrcAccessor> src,
2411 pair<DestIterator, DestAccessor> dest,
2412 double scale, GradValue gradient_threshold,
2413 DestValue edge_marker, bool addBorder = true);
2414 }
2415 \endcode
2416 \deprecatedEnd
2417
2418 <b> Usage:</b>
2419
2420 <b>\#include</b> <vigra/edgedetection.hxx><br>
2421 Namespace: vigra
2422
2423 \code
2424 MultiArray<2, unsigned char> src(w,h), edges(w,h);
2425 ...
2426
2427 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1, and add border
2428 cannyEdgeImageWithThinning(src, edges, 0.8, 4.0, 1, true);
2429 \endcode
2430
2431 \deprecatedUsage{cannyEdgeImageWithThinning}
2432 \code
2433 vigra::BImage src(w,h), edges(w,h);
2434
2435 // empty edge image
2436 edges = 0;
2437 ...
2438
2439 // find edges at scale 0.8 with gradient larger than 4.0, mark with 1, annd add border
2440 vigra::cannyEdgeImageWithThinning(srcImageRange(src), destImage(edges),
2441 0.8, 4.0, 1, true);
2442 \endcode
2443 <b> Required Interface:</b>
2444 see also: \ref cannyEdgelList().
2445 \code
2446 DestImageIterator dest_upperleft;
2447 DestAccessor dest_accessor;
2448 DestValue edge_marker;
2449
2450 dest_accessor.set(edge_marker, dest_upperleft, vigra::Diff2D(1,1));
2451 \endcode
2452 \deprecatedEnd
2453
2454 <b> Preconditions:</b>
2455
2456 \code
2457 scale > 0
2458 gradient_threshold > 0
2459 \endcode
2460 */
2461 doxygen_overloaded_function(template <...> void cannyEdgeImageWithThinning)
2462
2463 template <class SrcIterator, class SrcAccessor,
2464 class DestIterator, class DestAccessor,
2465 class GradValue, class DestValue>
2466 void cannyEdgeImageWithThinning(
2467 SrcIterator sul, SrcIterator slr, SrcAccessor sa,
2468 DestIterator dul, DestAccessor da,
2469 double scale, GradValue gradient_threshold,
2470 DestValue edge_marker, bool addBorder = true)
2471 {
2472 // mark pixels that are higher than their neighbors in gradient direction
2473 typedef typename NumericTraits<typename SrcAccessor::value_type>::RealPromote TmpType;
2474 BasicImage<TinyVector<TmpType, 2> > grad(slr-sul);
2475 gaussianGradient(srcIterRange(sul, slr, sa), destImage(grad), scale);
2476 cannyEdgeImageFromGradWithThinning(srcImageRange(grad), destIter(dul, da),
2477 gradient_threshold, edge_marker, addBorder);
2478 }
2479
2480 template <class SrcIterator, class SrcAccessor,
2481 class DestIterator, class DestAccessor,
2482 class GradValue, class DestValue>
2483 inline void
2484 cannyEdgeImageWithThinning(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2485 pair<DestIterator, DestAccessor> dest,
2486 double scale, GradValue gradient_threshold,
2487 DestValue edge_marker, bool addBorder = true)
2488 {
2489 cannyEdgeImageWithThinning(src.first, src.second, src.third,
2490 dest.first, dest.second,
2491 scale, gradient_threshold, edge_marker, addBorder);
2492 }
2493
2494 template <class T1, class S1,
2495 class T2, class S2,
2496 class GradValue, class DestValue>
2497 inline void
2498 cannyEdgeImageWithThinning(MultiArrayView<2, T1, S1> const & src,
2499 MultiArrayView<2, T2, S2> dest,
2500 double scale, GradValue gradient_threshold,
2501 DestValue edge_marker, bool addBorder = true)
2502 {
2503 vigra_precondition(src.shape() == dest.shape(),
2504 "cannyEdgeImageWithThinning(): shape mismatch between input and output.");
2505 cannyEdgeImageWithThinning(srcImageRange(src),
2506 destImage(dest),
2507 scale, gradient_threshold, edge_marker, addBorder);
2508 }
2509
2510 /********************************************************/
2511
2512 template <class SrcIterator, class SrcAccessor,
2513 class MaskImage, class BackInsertable, class GradValue>
2514 void internalCannyFindEdgels3x3(SrcIterator ul, SrcAccessor grad,
2515 MaskImage const & mask,
2516 BackInsertable & edgels,
2517 GradValue grad_thresh)
2518 {
2519 typedef typename SrcAccessor::value_type PixelType;
2520 typedef typename PixelType::value_type ValueType;
2521
2522 vigra_precondition(grad_thresh >= NumericTraits<GradValue>::zero(),
2523 "cannyFindEdgels3x3(): gradient threshold must not be negative.");
2524
2525 ul += Diff2D(1,1);
2526 for(int y=1; y<mask.height()-1; ++y, ++ul.y)
2527 {
2528 SrcIterator ix = ul;
2529 for(int x=1; x<mask.width()-1; ++x, ++ix.x)
2530 {
2531 if(!mask(x,y))
2532 continue;
2533
2534 ValueType gradx = grad.getComponent(ix, 0);
2535 ValueType grady = grad.getComponent(ix, 1);
2536 double mag = hypot(gradx, grady);
2537 if(mag <= grad_thresh)
2538 continue;
2539 double c = gradx / mag,
2540 s = grady / mag;
2541
2542 Matrix<double> ml(3,3), mr(3,1), l(3,1), r(3,1);
2543 l(0,0) = 1.0;
2544
2545 for(int yy = -1; yy <= 1; ++yy)
2546 {
2547 for(int xx = -1; xx <= 1; ++xx)
2548 {
2549 double u = c*xx + s*yy;
2550 double v = norm(grad(ix, Diff2D(xx, yy)));
2551 l(1,0) = u;
2552 l(2,0) = u*u;
2553 ml += outer(l);
2554 mr += v*l;
2555 }
2556 }
2557
2558 linearSolve(ml, mr, r);
2559
2560 Edgel edgel;
2561
2562 // local maximum => quadratic interpolation of sub-pixel location
2563 double del = -r(1,0) / 2.0 / r(2,0);
2564 if(std::fabs(del) > 1.5) // don't move by more than about a pixel diameter
2565 del = 0.0;
2566 edgel.x = Edgel::value_type(x + c*del);
2567 edgel.y = Edgel::value_type(y + s*del);
2568 edgel.strength = Edgel::value_type(mag);
2569 double orientation = VIGRA_CSTD::atan2(grady, gradx) + 0.5*M_PI;
2570 if(orientation < 0.0)
2571 orientation += 2.0*M_PI;
2572 edgel.orientation = Edgel::value_type(orientation);
2573 edgels.push_back(edgel);
2574 }
2575 }
2576 }
2577
2578 /********************************************************/
2579 /* */
2580 /* cannyEdgelList3x3 */
2581 /* */
2582 /********************************************************/
2583
2584 /** \brief Improved implementation of Canny's edge detector.
2585
2586 This operator first computes pixels which are crossed by the edge using
2587 cannyEdgeImageWithThinning(). The gradient magnitudes in the 3x3 neighborhood of these
2588 pixels are then projected onto the normal of the edge (as determined
2589 by the gradient direction). The edgel's subpixel location is found by fitting a
2590 parabola through the 9 gradient values and determining the parabola's tip.
2591 A new \ref Edgel is appended to the given vector of <TT>edgels</TT>. Since the parabola
2592 is fitted to 9 points rather than 3 points as in cannyEdgelList(), the accuracy is higher.
2593
2594 The function can be called in two modes: If you pass a 'scale', it is assumed that the
2595 original image is scalar, and the Gaussian gradient is internally computed at the
2596 given 'scale'. If the function is called without scale parameter, it is assumed that
2597 the given image already contains the gradient (i.e. its value_type must be
2598 a vector of length 2).
2599
2600 <b> Declarations:</b>
2601
2602 pass 2D array views:
2603 \code
2604 namespace vigra {
2605 // compute edgels from a scalar image (determine gradient internally at 'scale')
2606 template <class T, class S, class BackInsertable>
2607 void
2608 cannyEdgelList3x3(MultiArrayView<2, T, S> const & src,
2609 BackInsertable & edgels,
2610 double scale);
2611
2612 // compute edgels from a pre-computed gradient image
2613 template <class T, class S, class BackInsertable>
2614 void
2615 cannyEdgelList3x3(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
2616 BackInsertable & edgels);
2617 }
2618 \endcode
2619
2620 \deprecatedAPI{cannyEdgelList3x3}
2621 pass \ref ImageIterators and \ref DataAccessors :
2622 \code
2623 namespace vigra {
2624 // compute edgels from a gradient image
2625 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2626 void cannyEdgelList3x3(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2627 BackInsertable & edgels);
2628
2629 // compute edgels from a scalar image (determine gradient internally at 'scale')
2630 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2631 void cannyEdgelList3x3(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2632 BackInsertable & edgels, double scale);
2633 }
2634 \endcode
2635 use argument objects in conjunction with \ref ArgumentObjectFactories :
2636 \code
2637 namespace vigra {
2638 // compute edgels from a gradient image
2639 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2640 void
2641 cannyEdgelList3x3(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2642 BackInsertable & edgels);
2643
2644 // compute edgels from a scalar image (determine gradient internally at 'scale')
2645 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2646 void
2647 cannyEdgelList3x3(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2648 BackInsertable & edgels, double scale);
2649 }
2650 \endcode
2651 \deprecatedEnd
2652
2653 <b> Usage:</b>
2654
2655 <b>\#include</b> <vigra/edgedetection.hxx><br>
2656 Namespace: vigra
2657
2658 \code
2659 MultiArray<2, unsigned char> src(w,h);
2660
2661 // create empty edgel list
2662 std::vector<vigra::Edgel> edgels;
2663 ...
2664
2665 // find edgels at scale 0.8
2666 cannyEdgelList3x3(src, edgels, 0.8);
2667 \endcode
2668
2669 \deprecatedUsage{cannyEdgelList3x3}
2670 \code
2671 vigra::BImage src(w,h);
2672
2673 // empty edgel list
2674 std::vector<vigra::Edgel> edgels;
2675 ...
2676
2677 // find edgels at scale 0.8
2678 vigra::cannyEdgelList3x3(srcImageRange(src), edgels, 0.8);
2679 \endcode
2680 <b> Required Interface:</b>
2681 \code
2682 SrcImageIterator src_upperleft;
2683 SrcAccessor src_accessor;
2684
2685 src_accessor(src_upperleft);
2686
2687 BackInsertable edgels;
2688 edgels.push_back(Edgel());
2689 \endcode
2690 SrcAccessor::value_type must be a type convertible to float
2691 \deprecatedEnd
2692
2693 <b> Preconditions:</b>
2694
2695 \code
2696 scale > 0
2697 \endcode
2698 */
2699 doxygen_overloaded_function(template <...> void cannyEdgelList3x3)
2700
2701 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2702 void
2703 cannyEdgelList3x3(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2704 BackInsertable & edgels, double scale)
2705 {
2706 typedef typename NumericTraits<typename SrcAccessor::value_type>::RealPromote TmpType;
2707 BasicImage<TinyVector<TmpType, 2> > grad(lr-ul);
2708 gaussianGradient(srcIterRange(ul, lr, src), destImage(grad), scale);
2709
2710 cannyEdgelList3x3(srcImageRange(grad), edgels);
2711 }
2712
2713 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2714 void
2715 cannyEdgelList3x3(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2716 BackInsertable & edgels)
2717 {
2718 typedef typename NormTraits<typename SrcAccessor::value_type>::NormType NormType;
2719
2720 UInt8Image edges(lr-ul);
2721 cannyEdgeImageFromGradWithThinning(srcIterRange(ul, lr, src), destImage(edges),
2722 0.0, 1, false);
2723
2724 // find edgels
2725 internalCannyFindEdgels3x3(ul, src, edges, edgels, NumericTraits<NormType>::zero());
2726 }
2727
2728 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2729 inline void
2730 cannyEdgelList3x3(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2731 BackInsertable & edgels, double scale)
2732 {
2733 cannyEdgelList3x3(src.first, src.second, src.third, edgels, scale);
2734 }
2735
2736 template <class SrcIterator, class SrcAccessor, class BackInsertable>
2737 inline void
2738 cannyEdgelList3x3(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2739 BackInsertable & edgels)
2740 {
2741 cannyEdgelList3x3(src.first, src.second, src.third, edgels);
2742 }
2743
2744 template <class T, class S, class BackInsertable>
2745 inline void
2746 cannyEdgelList3x3(MultiArrayView<2, T, S> const & src,
2747 BackInsertable & edgels, double scale)
2748 {
2749 cannyEdgelList3x3(srcImageRange(src), edgels, scale);
2750 }
2751
2752 template <class T, class S, class BackInsertable>
2753 inline void
2754 cannyEdgelList3x3(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
2755 BackInsertable & edgels)
2756 {
2757 cannyEdgelList3x3(srcImageRange(src), edgels);
2758 }
2759
2760 /********************************************************/
2761 /* */
2762 /* cannyEdgelList3x3Threshold */
2763 /* */
2764 /********************************************************/
2765
2766 /** \brief Improved implementation of Canny's edge detector with thresholding.
2767
2768 This function works exactly like \ref cannyEdgelList3x3(), but
2769 you also pass a threshold for the minimal gradient magnitude,
2770 so that edgels whose strength is below the threshold are not
2771 inserted into the edgel list.
2772
2773 <b> Declarations:</b>
2774
2775 pass 2D array views:
2776 \code
2777 namespace vigra {
2778 // compute edgels from a gradient image
2779 template <class SrcIterator, class SrcAccessor,
2780 class BackInsertable, class GradValue>
2781 void
2782 cannyEdgelList3x3Threshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2783 BackInsertable & edgels, GradValue grad_thresh);
2784
2785 // compute edgels from a scalar image (determine gradient internally at 'scale')
2786 template <class SrcIterator, class SrcAccessor,
2787 class BackInsertable, class GradValue>
2788 void
2789 cannyEdgelList3x3Threshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2790 BackInsertable & edgels, double scale, GradValue grad_thresh);
2791 }
2792 \endcode
2793
2794 \deprecatedAPI{cannyEdgelList3x3Threshold}
2795 pass \ref ImageIterators and \ref DataAccessors :
2796 \code
2797 namespace vigra {
2798 // compute edgels from a gradient image
2799 template <class SrcIterator, class SrcAccessor,
2800 class BackInsertable, class GradValue>
2801 void
2802 cannyEdgelList3x3Threshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2803 BackInsertable & edgels, GradValue grad_thresh);
2804
2805 // compute edgels from a scalar image (determine gradient internally at 'scale')
2806 template <class SrcIterator, class SrcAccessor,
2807 class BackInsertable, class GradValue>
2808 void
2809 cannyEdgelList3x3Threshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2810 BackInsertable & edgels, double scale, GradValue grad_thresh);
2811 }
2812 \endcode
2813 use argument objects in conjunction with \ref ArgumentObjectFactories :
2814 \code
2815 namespace vigra {
2816 // compute edgels from a gradient image
2817 template <class SrcIterator, class SrcAccessor,
2818 class BackInsertable, class GradValue>
2819 void
2820 cannyEdgelList3x3Threshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2821 BackInsertable & edgels, GradValue grad_thresh);
2822
2823 // compute edgels from a scalar image (determine gradient internally at 'scale')
2824 template <class SrcIterator, class SrcAccessor,
2825 class BackInsertable, class GradValue>
2826 void
2827 cannyEdgelList3x3Threshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2828 BackInsertable & edgels, double scale, GradValue grad_thresh);
2829 }
2830 \endcode
2831 \deprecatedEnd
2832
2833 <b> Usage:</b>
2834
2835 <b>\#include</b> <vigra/edgedetection.hxx><br>
2836 Namespace: vigra
2837
2838 \code
2839 MultiArray<2, unsigned char> src(w,h);
2840
2841 // create empty edgel list
2842 std::vector<vigra::Edgel> edgels;
2843 ...
2844
2845 // find edgels at scale 0.8 whose gradient is at least 4.0
2846 cannyEdgelList3x3Threshold(src, edgels, 0.8, 4.0);
2847 \endcode
2848
2849 \deprecatedUsage{cannyEdgelList3x3Threshold}
2850 \code
2851 vigra::BImage src(w,h);
2852
2853 // empty edgel list
2854 std::vector<vigra::Edgel> edgels;
2855 ...
2856
2857 // find edgels at scale 0.8 whose gradient is at least 4.0
2858 vigra::cannyEdgelList3x3Threshold(srcImageRange(src), edgels, 0.8, 4.0);
2859 \endcode
2860 <b> Required Interface:</b>
2861 \code
2862 SrcImageIterator src_upperleft;
2863 SrcAccessor src_accessor;
2864
2865 src_accessor(src_upperleft);
2866
2867 BackInsertable edgels;
2868 edgels.push_back(Edgel());
2869 \endcode
2870 SrcAccessor::value_type must be a type convertible to float
2871 \deprecatedEnd
2872
2873 <b> Preconditions:</b>
2874
2875 \code
2876 scale > 0
2877 \endcode
2878 */
2879 doxygen_overloaded_function(template <...> void cannyEdgelList3x3Threshold)
2880
2881 template <class SrcIterator, class SrcAccessor,
2882 class BackInsertable, class GradValue>
2883 void
2884 cannyEdgelList3x3Threshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2885 BackInsertable & edgels, double scale, GradValue grad_thresh)
2886 {
2887 typedef typename NumericTraits<typename SrcAccessor::value_type>::RealPromote TmpType;
2888 BasicImage<TinyVector<TmpType, 2> > grad(lr-ul);
2889 gaussianGradient(srcIterRange(ul, lr, src), destImage(grad), scale);
2890
2891 cannyEdgelList3x3Threshold(srcImageRange(grad), edgels, grad_thresh);
2892 }
2893
2894 template <class SrcIterator, class SrcAccessor,
2895 class BackInsertable, class GradValue>
2896 void
2897 cannyEdgelList3x3Threshold(SrcIterator ul, SrcIterator lr, SrcAccessor src,
2898 BackInsertable & edgels, GradValue grad_thresh)
2899 {
2900 UInt8Image edges(lr-ul);
2901 cannyEdgeImageFromGradWithThinning(srcIterRange(ul, lr, src), destImage(edges),
2902 0.0, 1, false);
2903
2904 // find edgels
2905 internalCannyFindEdgels3x3(ul, src, edges, edgels, grad_thresh);
2906 }
2907
2908 template <class SrcIterator, class SrcAccessor,
2909 class BackInsertable, class GradValue>
2910 inline void
2911 cannyEdgelList3x3Threshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2912 BackInsertable & edgels, double scale, GradValue grad_thresh)
2913 {
2914 cannyEdgelList3x3Threshold(src.first, src.second, src.third, edgels, scale, grad_thresh);
2915 }
2916
2917 template <class SrcIterator, class SrcAccessor,
2918 class BackInsertable, class GradValue>
2919 inline void
2920 cannyEdgelList3x3Threshold(triple<SrcIterator, SrcIterator, SrcAccessor> src,
2921 BackInsertable & edgels, GradValue grad_thresh)
2922 {
2923 cannyEdgelList3x3Threshold(src.first, src.second, src.third, edgels, grad_thresh);
2924 }
2925
2926 template <class T, class S,
2927 class BackInsertable, class GradValue>
2928 inline void
2929 cannyEdgelList3x3Threshold(MultiArrayView<2, T, S> const & src,
2930 BackInsertable & edgels, double scale, GradValue grad_thresh)
2931 {
2932 cannyEdgelList3x3Threshold(srcImageRange(src), edgels, scale, grad_thresh);
2933 }
2934
2935 template <class T, class S,
2936 class BackInsertable, class GradValue>
2937 inline void
2938 cannyEdgelList3x3Threshold(MultiArrayView<2, TinyVector<T, 2>, S> const & src,
2939 BackInsertable & edgels,
2940 GradValue grad_thresh)
2941 {
2942 cannyEdgelList3x3Threshold(srcImageRange(src), edgels, grad_thresh);
2943 }
2944
2945 //@}
2946
2947 /** \page CrackEdgeImage Crack Edge Image
2948
2949 Crack edges are marked <i>between</i> the pixels of an image.
2950 A Crack Edge Image is an image that represents these edges. In order
2951 to accommodate the cracks, the Crack Edge Image must be twice as large
2952 as the original image (precisely (2*w - 1) by (2*h - 1)). A Crack Edge Image
2953 can easily be derived from a binary image or from the signs of the
2954 response of a Laplacian filter. Consider the following sketch, where
2955 <TT>+</TT> encodes the foreground, <TT>-</TT> the background, and
2956 <TT>*</TT> the resulting crack edges.
2957
2958 \code
2959 sign of difference image insert cracks resulting CrackEdgeImage
2960
2961 + . - . - . * . . .
2962 + - - . . . . . . * * * .
2963 + + - => + . + . - => . . . * .
2964 + + + . . . . . . . . * *
2965 + . + . + . . . . .
2966 \endcode
2967
2968 Starting from the original binary image (left), we insert crack pixels
2969 to get to the double-sized image (center). Finally, we mark all
2970 crack pixels whose non-crack neighbors have different signs as
2971 crack edge points, while all other pixels (crack and non-crack) become
2972 region pixels.
2973
2974 <b>Requirements on a Crack Edge Image:</b>
2975
2976 <ul>
2977 <li>Crack Edge Images have odd width and height.
2978 <li>Crack pixels have at least one odd coordinate.
2979 <li>Only crack pixels may be marked as edge points.
2980 <li>Crack pixels with two odd coordinates must be marked as edge points
2981 whenever any of their neighboring crack pixels was marked.
2982 </ul>
2983
2984 The last two requirements ensure that both edges and regions are 4-connected.
2985 Thus, 4-connectivity and 8-connectivity yield identical connected
2986 components in a Crack Edge Image (so called <i>well-composedness</i>).
2987 This ensures that Crack Edge Images have nice topological properties
2988 (cf. L. J. Latecki: "Well-Composed Sets", Academic Press, 2000).
2989 */
2990
2991
2992 } // namespace vigra
2993
2994 #endif // VIGRA_EDGEDETECTION_HXX

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany | html generated using doxygen and Python vigra 1.10.0 (Mon Nov 18 2013)