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seededregiongrowing.hxx |

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2 /* */
3 /* Copyright 1998-2010 by Ullrich Koethe, Hans Meine */
4 /* */
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34 /************************************************************************/
35
36 #ifndef VIGRA_SEEDEDREGIONGROWING_HXX
37 #define VIGRA_SEEDEDREGIONGROWING_HXX
38
39 #include <vector>
40 #include <stack>
41 #include <queue>
42 #include "utilities.hxx"
43 #include "stdimage.hxx"
44 #include "stdimagefunctions.hxx"
45 #include "pixelneighborhood.hxx"
46 #include "bucket_queue.hxx"
47 #include "multi_shape.hxx"
48
49 namespace vigra {
50
51 namespace detail {
52
53 template <class COST>
54 class SeedRgPixel
55 {
56 public:
57 Point2D location_, nearest_;
58 COST cost_;
59 int count_;
60 int label_;
61 int dist_;
62
63 SeedRgPixel()
64 : location_(0,0), nearest_(0,0), cost_(0), count_(0), label_(0)
65 {}
66
67 SeedRgPixel(Point2D const & location, Point2D const & nearest,
68 COST const & cost, int const & count, int const & label)
69 : location_(location), nearest_(nearest),
70 cost_(cost), count_(count), label_(label)
71 {
72 int dx = location_.x - nearest_.x;
73 int dy = location_.y - nearest_.y;
74 dist_ = dx * dx + dy * dy;
75 }
76
77 void set(Point2D const & location, Point2D const & nearest,
78 COST const & cost, int const & count, int const & label)
79 {
80 location_ = location;
81 nearest_ = nearest;
82 cost_ = cost;
83 count_ = count;
84 label_ = label;
85
86 int dx = location_.x - nearest_.x;
87 int dy = location_.y - nearest_.y;
88 dist_ = dx * dx + dy * dy;
89 }
90
91 struct Compare
92 {
93 // must implement > since priority_queue looks for largest element
94 bool operator()(SeedRgPixel const & l,
95 SeedRgPixel const & r) const
96 {
97 if(r.cost_ == l.cost_)
98 {
99 if(r.dist_ == l.dist_) return r.count_ < l.count_;
100
101 return r.dist_ < l.dist_;
102 }
103
104 return r.cost_ < l.cost_;
105 }
106 bool operator()(SeedRgPixel const * l,
107 SeedRgPixel const * r) const
108 {
109 if(r->cost_ == l->cost_)
110 {
111 if(r->dist_ == l->dist_) return r->count_ < l->count_;
112
113 return r->dist_ < l->dist_;
114 }
115
116 return r->cost_ < l->cost_;
117 }
118 };
119
120 struct Allocator
121 {
122 ~Allocator()
123 {
124 while(!freelist_.empty())
125 {
126 delete freelist_.top();
127 freelist_.pop();
128 }
129 }
130
131 SeedRgPixel *
132 create(Point2D const & location, Point2D const & nearest,
133 COST const & cost, int const & count, int const & label)
134 {
135 if(!freelist_.empty())
136 {
137 SeedRgPixel * res = freelist_.top();
138 freelist_.pop();
139 res->set(location, nearest, cost, count, label);
140 return res;
141 }
142
143 return new SeedRgPixel(location, nearest, cost, count, label);
144 }
145
146 void dismiss(SeedRgPixel * p)
147 {
148 freelist_.push(p);
149 }
150
151 std::stack<SeedRgPixel<COST> *> freelist_;
152 };
153 };
154
155 struct UnlabelWatersheds
156 {
157 int operator()(int label) const
158 {
159 return label < 0 ? 0 : label;
160 }
161 };
162
163 } // namespace detail
164
165 /** \addtogroup SeededRegionGrowing Region Segmentation Algorithms
166 Region growing, watersheds, and voronoi tesselation
167 */
168 //@{
169
170 /********************************************************/
171 /* */
172 /* seededRegionGrowing */
173 /* */
174 /********************************************************/
175
176 /** Choose between different types of Region Growing */
177 enum SRGType {
178 CompleteGrow = 0,
179 KeepContours = 1,
180 StopAtThreshold = 2,
181 SRGWatershedLabel = -1
182 };
183
184 /** \brief Region Segmentation by means of Seeded Region Growing.
185
186 This algorithm implements seeded region growing as described in
187
188 R. Adams, L. Bischof: <em>"Seeded Region Growing"</em>, IEEE Trans. on Pattern
189 Analysis and Maschine Intelligence, vol 16, no 6, 1994, and
190
191 Ullrich K&ouml;the:
192 <em><a href="http://hci.iwr.uni-heidelberg.de/people/ukoethe/papers/index.php#cite_primary_segmentation">Primary Image Segmentation</a></em>,
193 in: G. Sagerer, S.
194 Posch, F. Kummert (eds.): Mustererkennung 1995, Proc. 17. DAGM-Symposium,
195 Springer 1995
196
197 The seed image is a partly segmented image which contains uniquely
198 labeled regions (the seeds) and unlabeled pixels (the candidates, label 0).
199 The highest seed label found in the seed image is returned by the algorithm.
200
201 Seed regions can be as large as you wish and as small as one pixel. If
202 there are no candidates, the algorithm will simply copy the seed image
203 into the output image. Otherwise it will aggregate the candidates into
204 the existing regions so that a cost function is minimized.
205 Candidates are taken from the neighborhood of the already assigned pixels,
206 where the type of neighborhood is determined by parameter <tt>neighborhood</tt>
207 which can take the values <tt>FourNeighborCode()</tt> (the default)
208 or <tt>EightNeighborCode()</tt>. The algorithm basically works as follows
209 (illustrated for 4-neighborhood, but 8-neighborhood works in the same way):
210
211 <ol>
212
213 <li> Find all candidate pixels that are 4-adjacent to a seed region.
214 Calculate the cost for aggregating each candidate into its adjacent region
215 and put the candidates into a priority queue.
216
217 <li> While( priority queue is not empty and termination criterion is not fulfilled)
218
219 <ol>
220
221 <li> Take the candidate with least cost from the queue. If it has not
222 already been merged, merge it with it's adjacent region.
223
224 <li> Put all candidates that are 4-adjacent to the pixel just processed
225 into the priority queue.
226
227 </ol>
228
229 </ol>
230
231 <tt>SRGType</tt> can take the following values:
232
233 <DL>
234 <DT><tt>CompleteGrow</tt> <DD> produce a complete tesselation of the volume (default).
235 <DT><tt>KeepContours</tt> <DD> keep a 1-voxel wide unlabeled contour between all regions.
236 <DT><tt>StopAtThreshold</tt> <DD> stop when the boundary indicator values exceed the
237 threshold given by parameter <tt>max_cost</tt>.
238 <DT><tt>KeepContours | StopAtThreshold</tt> <DD> keep 1-voxel wide contour and stop at given <tt>max_cost</tt>.
239 </DL>
240
241 The cost is determined jointly by the source image and the
242 region statistics functor. The source image contains feature values for each
243 pixel which will be used by the region statistics functor to calculate and
244 update statistics for each region and to calculate the cost for each
245 candidate. The <TT>RegionStatisticsArray</TT> must be compatible to the
246 \ref ArrayOfRegionStatistics functor and contains an <em> array</em> of
247 statistics objects for each region. The indices must correspond to the
248 labels of the seed regions. The statistics for the initial regions must have
249 been calculated prior to calling <TT>seededRegionGrowing()</TT> (for example by
250 means of \ref inspectTwoImagesIf()).
251
252 For each candidate
253 <TT>x</TT> that is adjacent to region <TT>i</TT>, the algorithm will call
254 <TT>stats[i].cost(as(x))</TT> to get the cost (where <TT>x</TT> is a <TT>SrcIterator</TT>
255 and <TT>as</TT> is
256 the SrcAccessor). When a candidate has been merged with a region, the
257 statistics are updated by calling <TT>stats[i].operator()(as(x))</TT>. Since
258 the <TT>RegionStatisticsArray</TT> is passed by reference, this will overwrite
259 the original statistics.
260
261 If a candidate could be merged into more than one regions with identical
262 cost, the algorithm will favour the nearest region. If <tt>StopAtThreshold</tt> is active,
263 and the cost of the current candidate at any point in the algorithm exceeds the optional
264 <tt>max_cost</tt> value (which defaults to <tt>NumericTraits<double>::max()</tt>),
265 region growing is aborted, and all voxels not yet assigned to a region remain unlabeled.
266
267 In some cases, the cost only depends on the feature value of the current
268 pixel. Then the update operation will simply be a no-op, and the <TT>cost()</TT>
269 function returns its argument. This behavior is implemented by the
270 \ref SeedRgDirectValueFunctor. With <tt>SRGType == KeepContours</tt>,
271 this is equivalent to the watershed algorithm.
272
273 <b> Declarations:</b>
274
275 pass 2D array views:
276 \code
277 namespace vigra {
278 template <class T1, class S1,
279 class TS, class AS,
280 class T2, class S2,
281 class RegionStatisticsArray, class Neighborhood>
282 TS
283 seededRegionGrowing(MultiArrayView<2, T1, S1> const & src,
284 MultiArrayView<2, TS, AS> const & seeds,
285 MultiArrayView<2, T2, S2> labels,
286 RegionStatisticsArray & stats,
287 SRGType srgType = CompleteGrow,
288 Neighborhood n = FourNeighborCode(),
289 double max_cost = NumericTraits<double>::max());
290 }
291 \endcode
292
293 \deprecatedAPI{seededRegionGrowing}
294 pass \ref ImageIterators and \ref DataAccessors :
295 \code
296 namespace vigra {
297 template <class SrcIterator, class SrcAccessor,
298 class SeedImageIterator, class SeedAccessor,
299 class DestIterator, class DestAccessor,
300 class RegionStatisticsArray, class Neighborhood>
301 typename SeedAccessor::value_type
302 seededRegionGrowing(SrcIterator srcul, SrcIterator srclr, SrcAccessor as,
303 SeedImageIterator seedsul, SeedAccessor aseeds,
304 DestIterator destul, DestAccessor ad,
305 RegionStatisticsArray & stats,
306 SRGType srgType = CompleteGrow,
307 Neighborhood neighborhood = FourNeighborCode(),
308 double max_cost = NumericTraits<double>::max());
309 }
310 \endcode
311 use argument objects in conjunction with \ref ArgumentObjectFactories :
312 \code
313 namespace vigra {
314 template <class SrcIterator, class SrcAccessor,
315 class SeedImageIterator, class SeedAccessor,
316 class DestIterator, class DestAccessor,
317 class RegionStatisticsArray, class Neighborhood>
318 typename SeedAccessor::value_type
319 seededRegionGrowing(triple<SrcIterator, SrcIterator, SrcAccessor> src,
320 pair<SeedImageIterator, SeedAccessor> seeds,
321 pair<DestIterator, DestAccessor> dest,
322 RegionStatisticsArray & stats,
323 SRGType srgType = CompleteGrow,
324 Neighborhood neighborhood = FourNeighborCode(),
325 double max_cost = NumericTraits<double>::max());
326 }
327 \endcode
328 \deprecatedEnd
329
330 <b> Usage:</b>
331
332 <b>\#include</b> <vigra/seededregiongrowing.hxx><br>
333 Namespace: vigra
334
335 Example: implementation of the voronoi tesselation
336
337 \code
338 MultiArray<2, int> points(w,h);
339 MultiArray<2, float> dist(x,y);
340
341 int max_region_label = 100;
342
343 // throw in some random points:
344 for(int i = 1; i <= max_region_label; ++i)
345 points(w * rand() / RAND_MAX , h * rand() / RAND_MAX) = i;
346
347 // calculate Euclidean distance transform
348 distanceTransform(points, dist, 2);
349
350 // init statistics functor
351 ArrayOfRegionStatistics<SeedRgDirectValueFunctor<float> > stats(max_region_label);
352
353 // find voronoi region of each point (the point image is overwritten with the
354 // voronoi region labels)
355 seededRegionGrowing(dist, points, points, stats);
356 \endcode
357
358 \deprecatedUsage{seededRegionGrowing}
359 \code
360 vigra::BImage points(w,h);
361 vigra::FImage dist(x,y);
362
363 // empty edge image
364 points = 0;
365 dist = 0;
366
367 int max_region_label = 100;
368
369 // throw in some random points:
370 for(int i = 1; i <= max_region_label; ++i)
371 points(w * rand() / RAND_MAX , h * rand() / RAND_MAX) = i;
372
373 // calculate Euclidean distance transform
374 vigra::distanceTransform(srcImageRange(points), destImage(dist), 2);
375
376 // init statistics functor
377 vigra::ArrayOfRegionStatistics<vigra::SeedRgDirectValueFunctor<float> >
378 stats(max_region_label);
379
380 // find voronoi region of each point
381 vigra:: seededRegionGrowing(srcImageRange(dist), srcImage(points),
382 destImage(points), stats);
383 \endcode
384 <b> Required Interface:</b>
385 \code
386 SrcIterator src_upperleft, src_lowerright;
387 SeedImageIterator seed_upperleft;
388 DestIterator dest_upperleft;
389
390 SrcAccessor src_accessor;
391 SeedAccessor seed_accessor;
392 DestAccessor dest_accessor;
393
394 RegionStatisticsArray stats;
395
396 // calculate costs
397 RegionStatisticsArray::value_type::cost_type cost =
398 stats[seed_accessor(seed_upperleft)].cost(src_accessor(src_upperleft));
399
400 // compare costs
401 cost < cost;
402
403 // update statistics
404 stats[seed_accessor(seed_upperleft)](src_accessor(src_upperleft));
405
406 // set result
407 dest_accessor.set(seed_accessor(seed_upperleft), dest_upperleft);
408 \endcode
409 \deprecatedEnd
410
411 Further requirements are determined by the <TT>RegionStatisticsArray</TT>.
412 */
413 doxygen_overloaded_function(template <...> void seededRegionGrowing)
414
415 template <class SrcIterator, class SrcAccessor,
416 class SeedImageIterator, class SeedAccessor,
417 class DestIterator, class DestAccessor,
418 class RegionStatisticsArray, class Neighborhood>
419 typename SeedAccessor::value_type
420 seededRegionGrowing(SrcIterator srcul,
421 SrcIterator srclr, SrcAccessor as,
422 SeedImageIterator seedsul, SeedAccessor aseeds,
423 DestIterator destul, DestAccessor ad,
424 RegionStatisticsArray & stats,
425 SRGType srgType,
426 Neighborhood,
427 double max_cost)
428 {
429 int w = srclr.x - srcul.x;
430 int h = srclr.y - srcul.y;
431 int count = 0;
432
433 SrcIterator isy = srcul, isx = srcul; // iterators for the src image
434
435 typedef typename SeedAccessor::value_type LabelType;
436 typedef typename RegionStatisticsArray::value_type RegionStatistics;
437 typedef typename RegionStatistics::cost_type CostType;
438 typedef detail::SeedRgPixel<CostType> Pixel;
439
440 typename Pixel::Allocator allocator;
441
442 typedef std::priority_queue<Pixel *, std::vector<Pixel *>,
443 typename Pixel::Compare> SeedRgPixelHeap;
444
445 // copy seed image in an image with border
446 IImage regions(w+2, h+2);
447 IImage::Iterator ir = regions.upperLeft() + Diff2D(1,1);
448 IImage::Iterator iry, irx;
449
450 initImageBorder(destImageRange(regions), 1, SRGWatershedLabel);
451 copyImage(seedsul, seedsul+Diff2D(w,h), aseeds, ir, regions.accessor());
452
453 // allocate and init memory for the results
454
455 SeedRgPixelHeap pheap;
456 int cneighbor, maxRegionLabel = 0;
457
458 typedef typename Neighborhood::Direction Direction;
459 int directionCount = Neighborhood::DirectionCount;
460
461 Point2D pos(0,0);
462 for(isy=srcul, iry=ir, pos.y=0; pos.y<h;
463 ++pos.y, ++isy.y, ++iry.y)
464 {
465 for(isx=isy, irx=iry, pos.x=0; pos.x<w;
466 ++pos.x, ++isx.x, ++irx.x)
467 {
468 if(*irx == 0)
469 {
470 // find candidate pixels for growing and fill heap
471 for(int i=0; i<directionCount; i++)
472 {
473 // cneighbor = irx[dist[i]];
474 cneighbor = irx[Neighborhood::diff((Direction)i)];
475 if(cneighbor > 0)
476 {
477 CostType cost = stats[cneighbor].cost(as(isx));
478
479 Pixel * pixel =
480 allocator.create(pos, pos+Neighborhood::diff((Direction)i), cost, count++, cneighbor);
481 pheap.push(pixel);
482 }
483 }
484 }
485 else
486 {
487 vigra_precondition((LabelType)*irx <= stats.maxRegionLabel(),
488 "seededRegionGrowing(): Largest label exceeds size of RegionStatisticsArray.");
489 if(maxRegionLabel < *irx)
490 maxRegionLabel = *irx;
491 }
492 }
493 }
494
495 // perform region growing
496 while(pheap.size() != 0)
497 {
498 Pixel * pixel = pheap.top();
499 pheap.pop();
500
501 Point2D pos = pixel->location_;
502 Point2D nearest = pixel->nearest_;
503 int lab = pixel->label_;
504 CostType cost = pixel->cost_;
505
506 allocator.dismiss(pixel);
507
508 if((srgType & StopAtThreshold) != 0 && cost > max_cost)
509 break;
510
511 irx = ir + pos;
512 isx = srcul + pos;
513
514 if(*irx) // already labelled region / watershed?
515 continue;
516
517 if((srgType & KeepContours) != 0)
518 {
519 for(int i=0; i<directionCount; i++)
520 {
521 cneighbor = irx[Neighborhood::diff((Direction)i)];
522 if((cneighbor>0) && (cneighbor != lab))
523 {
524 lab = SRGWatershedLabel;
525 break;
526 }
527 }
528 }
529
530 *irx = lab;
531
532 if((srgType & KeepContours) == 0 || lab > 0)
533 {
534 // update statistics
535 stats[*irx](as(isx));
536
537 // search neighborhood
538 // second pass: find new candidate pixels
539 for(int i=0; i<directionCount; i++)
540 {
541 if(irx[Neighborhood::diff((Direction)i)] == 0)
542 {
543 CostType cost = stats[lab].cost(as(isx, Neighborhood::diff((Direction)i)));
544
545 Pixel * new_pixel =
546 allocator.create(pos+Neighborhood::diff((Direction)i), nearest, cost, count++, lab);
547 pheap.push(new_pixel);
548 }
549 }
550 }
551 }
552
553 // free temporary memory
554 while(pheap.size() != 0)
555 {
556 allocator.dismiss(pheap.top());
557 pheap.pop();
558 }
559
560 // write result
561 transformImage(ir, ir+Point2D(w,h), regions.accessor(), destul, ad,
562 detail::UnlabelWatersheds());
563
564 return (LabelType)maxRegionLabel;
565 }
566
567 template <class SrcIterator, class SrcAccessor,
568 class SeedImageIterator, class SeedAccessor,
569 class DestIterator, class DestAccessor,
570 class RegionStatisticsArray, class Neighborhood>
571 inline typename SeedAccessor::value_type
572 seededRegionGrowing(SrcIterator srcul,
573 SrcIterator srclr, SrcAccessor as,
574 SeedImageIterator seedsul, SeedAccessor aseeds,
575 DestIterator destul, DestAccessor ad,
576 RegionStatisticsArray & stats,
577 SRGType srgType,
578 Neighborhood n)
579 {
580 return seededRegionGrowing(srcul, srclr, as,
581 seedsul, aseeds,
582 destul, ad,
583 stats, srgType, n, NumericTraits<double>::max());
584 }
585
586
587
588 template <class SrcIterator, class SrcAccessor,
589 class SeedImageIterator, class SeedAccessor,
590 class DestIterator, class DestAccessor,
591 class RegionStatisticsArray>
592 inline typename SeedAccessor::value_type
593 seededRegionGrowing(SrcIterator srcul,
594 SrcIterator srclr, SrcAccessor as,
595 SeedImageIterator seedsul, SeedAccessor aseeds,
596 DestIterator destul, DestAccessor ad,
597 RegionStatisticsArray & stats,
598 SRGType srgType)
599 {
600 return seededRegionGrowing(srcul, srclr, as,
601 seedsul, aseeds,
602 destul, ad,
603 stats, srgType, FourNeighborCode());
604 }
605
606 template <class SrcIterator, class SrcAccessor,
607 class SeedImageIterator, class SeedAccessor,
608 class DestIterator, class DestAccessor,
609 class RegionStatisticsArray>
610 inline typename SeedAccessor::value_type
611 seededRegionGrowing(SrcIterator srcul,
612 SrcIterator srclr, SrcAccessor as,
613 SeedImageIterator seedsul, SeedAccessor aseeds,
614 DestIterator destul, DestAccessor ad,
615 RegionStatisticsArray & stats)
616 {
617 return seededRegionGrowing(srcul, srclr, as,
618 seedsul, aseeds,
619 destul, ad,
620 stats, CompleteGrow);
621 }
622
623 template <class SrcIterator, class SrcAccessor,
624 class SeedImageIterator, class SeedAccessor,
625 class DestIterator, class DestAccessor,
626 class RegionStatisticsArray, class Neighborhood>
627 inline typename SeedAccessor::value_type
628 seededRegionGrowing(triple<SrcIterator, SrcIterator, SrcAccessor> img1,
629 pair<SeedImageIterator, SeedAccessor> img3,
630 pair<DestIterator, DestAccessor> img4,
631 RegionStatisticsArray & stats,
632 SRGType srgType,
633 Neighborhood n,
634 double max_cost = NumericTraits<double>::max())
635 {
636 return seededRegionGrowing(img1.first, img1.second, img1.third,
637 img3.first, img3.second,
638 img4.first, img4.second,
639 stats, srgType, n, max_cost);
640 }
641
642 template <class SrcIterator, class SrcAccessor,
643 class SeedImageIterator, class SeedAccessor,
644 class DestIterator, class DestAccessor,
645 class RegionStatisticsArray>
646 inline typename SeedAccessor::value_type
647 seededRegionGrowing(triple<SrcIterator, SrcIterator, SrcAccessor> img1,
648 pair<SeedImageIterator, SeedAccessor> img3,
649 pair<DestIterator, DestAccessor> img4,
650 RegionStatisticsArray & stats,
651 SRGType srgType)
652 {
653 return seededRegionGrowing(img1.first, img1.second, img1.third,
654 img3.first, img3.second,
655 img4.first, img4.second,
656 stats, srgType, FourNeighborCode());
657 }
658
659 template <class SrcIterator, class SrcAccessor,
660 class SeedImageIterator, class SeedAccessor,
661 class DestIterator, class DestAccessor,
662 class RegionStatisticsArray>
663 inline typename SeedAccessor::value_type
664 seededRegionGrowing(triple<SrcIterator, SrcIterator, SrcAccessor> img1,
665 pair<SeedImageIterator, SeedAccessor> img3,
666 pair<DestIterator, DestAccessor> img4,
667 RegionStatisticsArray & stats)
668 {
669 return seededRegionGrowing(img1.first, img1.second, img1.third,
670 img3.first, img3.second,
671 img4.first, img4.second,
672 stats, CompleteGrow);
673 }
674
675 template <class T1, class S1,
676 class TS, class AS,
677 class T2, class S2,
678 class RegionStatisticsArray, class Neighborhood>
679 inline TS
680 seededRegionGrowing(MultiArrayView<2, T1, S1> const & img1,
681 MultiArrayView<2, TS, AS> const & img3,
682 MultiArrayView<2, T2, S2> img4,
683 RegionStatisticsArray & stats,
684 SRGType srgType,
685 Neighborhood n,
686 double max_cost = NumericTraits<double>::max())
687 {
688 vigra_precondition(img1.shape() == img3.shape(),
689 "seededRegionGrowing(): shape mismatch between input and output.");
690 return seededRegionGrowing(srcImageRange(img1),
691 srcImage(img3),
692 destImage(img4),
693 stats, srgType, n, max_cost);
694 }
695
696 template <class T1, class S1,
697 class TS, class AS,
698 class T2, class S2,
699 class RegionStatisticsArray>
700 inline TS
701 seededRegionGrowing(MultiArrayView<2, T1, S1> const & img1,
702 MultiArrayView<2, TS, AS> const & img3,
703 MultiArrayView<2, T2, S2> img4,
704 RegionStatisticsArray & stats,
705 SRGType srgType)
706 {
707 vigra_precondition(img1.shape() == img3.shape(),
708 "seededRegionGrowing(): shape mismatch between input and output.");
709 return seededRegionGrowing(srcImageRange(img1),
710 srcImage(img3),
711 destImage(img4),
712 stats, srgType, FourNeighborCode());
713 }
714
715 template <class T1, class S1,
716 class TS, class AS,
717 class T2, class S2,
718 class RegionStatisticsArray>
719 inline TS
720 seededRegionGrowing(MultiArrayView<2, T1, S1> const & img1,
721 MultiArrayView<2, TS, AS> const & img3,
722 MultiArrayView<2, T2, S2> img4,
723 RegionStatisticsArray & stats)
724 {
725 vigra_precondition(img1.shape() == img3.shape(),
726 "seededRegionGrowing(): shape mismatch between input and output.");
727 return seededRegionGrowing(srcImageRange(img1),
728 srcImage(img3),
729 destImage(img4),
730 stats, CompleteGrow);
731 }
732
733 /********************************************************/
734 /* */
735 /* fastSeededRegionGrowing */
736 /* */
737 /********************************************************/
738
739 template <class SrcIterator, class SrcAccessor,
740 class DestIterator, class DestAccessor,
741 class RegionStatisticsArray, class Neighborhood>
742 typename DestAccessor::value_type
743 fastSeededRegionGrowing(SrcIterator srcul, SrcIterator srclr, SrcAccessor as,
744 DestIterator destul, DestAccessor ad,
745 RegionStatisticsArray & stats,
746 SRGType srgType,
747 Neighborhood,
748 double max_cost,
749 std::ptrdiff_t bucket_count = 256)
750 {
751 typedef typename DestAccessor::value_type LabelType;
752
753 vigra_precondition((srgType & KeepContours) == 0,
754 "fastSeededRegionGrowing(): the turbo algorithm doesn't support 'KeepContours', sorry.");
755
756 int w = srclr.x - srcul.x;
757 int h = srclr.y - srcul.y;
758
759 SrcIterator isy = srcul, isx = srcul; // iterators for the src image
760 DestIterator idy = destul, idx = destul; // iterators for the dest image
761
762 BucketQueue<Point2D, true> pqueue(bucket_count);
763 LabelType maxRegionLabel = 0;
764
765 Point2D pos(0,0);
766 for(isy=srcul, idy = destul, pos.y=0; pos.y<h; ++pos.y, ++isy.y, ++idy.y)
767 {
768 for(isx=isy, idx=idy, pos.x=0; pos.x<w; ++pos.x, ++isx.x, ++idx.x)
769 {
770 LabelType label = ad(idx);
771 if(label != 0)
772 {
773 vigra_precondition(label <= stats.maxRegionLabel(),
774 "fastSeededRegionGrowing(): Largest label exceeds size of RegionStatisticsArray.");
775
776 if(maxRegionLabel < label)
777 maxRegionLabel = label;
778
779 AtImageBorder atBorder = isAtImageBorder(pos.x, pos.y, w, h);
780 if(atBorder == NotAtBorder)
781 {
782 NeighborhoodCirculator<DestIterator, Neighborhood> c(idx), cend(c);
783 do
784 {
785 if(ad(c) == 0)
786 {
787 std::ptrdiff_t priority = (std::ptrdiff_t)stats[label].cost(as(isx));
788 pqueue.push(pos, priority);
789 break;
790 }
791 }
792 while(++c != cend);
793 }
794 else
795 {
796 RestrictedNeighborhoodCirculator<DestIterator, Neighborhood>
797 c(idx, atBorder), cend(c);
798 do
799 {
800 if(ad(c) == 0)
801 {
802 std::ptrdiff_t priority = (std::ptrdiff_t)stats[label].cost(as(isx));
803 pqueue.push(pos, priority);
804 break;
805 }
806 }
807 while(++c != cend);
808 }
809 }
810 }
811 }
812
813 // perform region growing
814 while(!pqueue.empty())
815 {
816 Point2D pos = pqueue.top();
817 std::ptrdiff_t cost = pqueue.topPriority();
818 pqueue.pop();
819
820 if((srgType & StopAtThreshold) != 0 && cost > max_cost)
821 break;
822
823 idx = destul + pos;
824 isx = srcul + pos;
825
826 std::ptrdiff_t label = ad(idx);
827
828 AtImageBorder atBorder = isAtImageBorder(pos.x, pos.y, w, h);
829 if(atBorder == NotAtBorder)
830 {
831 NeighborhoodCirculator<DestIterator, Neighborhood> c(idx), cend(c);
832
833 do
834 {
835 std::ptrdiff_t nlabel = ad(c);
836 if(nlabel == 0)
837 {
838 ad.set(label, idx, c.diff());
839 std::ptrdiff_t priority =
840 std::max((std::ptrdiff_t)stats[label].cost(as(isx, c.diff())), cost);
841 pqueue.push(pos+c.diff(), priority);
842 }
843 }
844 while(++c != cend);
845 }
846 else
847 {
848 RestrictedNeighborhoodCirculator<DestIterator, Neighborhood>
849 c(idx, atBorder), cend(c);
850 do
851 {
852 std::ptrdiff_t nlabel = ad(c);
853 if(nlabel == 0)
854 {
855 ad.set(label, idx, c.diff());
856 std::ptrdiff_t priority =
857 std::max((std::ptrdiff_t)stats[label].cost(as(isx, c.diff())), cost);
858 pqueue.push(pos+c.diff(), priority);
859 }
860 }
861 while(++c != cend);
862 }
863 }
864
865 return maxRegionLabel;
866 }
867
868 template <class SrcIterator, class SrcAccessor,
869 class DestIterator, class DestAccessor,
870 class RegionStatisticsArray, class Neighborhood>
871 inline typename DestAccessor::value_type
872 fastSeededRegionGrowing(SrcIterator srcul, SrcIterator srclr, SrcAccessor as,
873 DestIterator destul, DestAccessor ad,
874 RegionStatisticsArray & stats,
875 SRGType srgType,
876 Neighborhood n)
877 {
878 return fastSeededRegionGrowing(srcul, srclr, as,
879 destul, ad,
880 stats, srgType, n, NumericTraits<double>::max(), 256);
881 }
882
883 template <class SrcIterator, class SrcAccessor,
884 class DestIterator, class DestAccessor,
885 class RegionStatisticsArray>
886 inline typename DestAccessor::value_type
887 fastSeededRegionGrowing(SrcIterator srcul, SrcIterator srclr, SrcAccessor as,
888 DestIterator destul, DestAccessor ad,
889 RegionStatisticsArray & stats,
890 SRGType srgType)
891 {
892 return fastSeededRegionGrowing(srcul, srclr, as,
893 destul, ad,
894 stats, srgType, FourNeighborCode());
895 }
896
897 template <class SrcIterator, class SrcAccessor,
898 class DestIterator, class DestAccessor,
899 class RegionStatisticsArray>
900 inline typename DestAccessor::value_type
901 fastSeededRegionGrowing(SrcIterator srcul, SrcIterator srclr, SrcAccessor as,
902 DestIterator destul, DestAccessor ad,
903 RegionStatisticsArray & stats)
904 {
905 return fastSeededRegionGrowing(srcul, srclr, as,
906 destul, ad,
907 stats, CompleteGrow);
908 }
909
910 template <class SrcIterator, class SrcAccessor,
911 class DestIterator, class DestAccessor,
912 class RegionStatisticsArray, class Neighborhood>
913 inline typename DestAccessor::value_type
914 fastSeededRegionGrowing(triple<SrcIterator, SrcIterator, SrcAccessor> src,
915 pair<DestIterator, DestAccessor> dest,
916 RegionStatisticsArray & stats,
917 SRGType srgType,
918 Neighborhood n,
919 double max_cost,
920 std::ptrdiff_t bucket_count = 256)
921 {
922 return fastSeededRegionGrowing(src.first, src.second, src.third,
923 dest.first, dest.second,
924 stats, srgType, n, max_cost, bucket_count);
925 }
926
927 template <class T1, class S1,
928 class T2, class S2,
929 class RegionStatisticsArray, class Neighborhood>
930 inline T2
931 fastSeededRegionGrowing(MultiArrayView<2, T1, S1> const & src,
932 MultiArrayView<2, T2, S2> dest,
933 RegionStatisticsArray & stats,
934 SRGType srgType,
935 Neighborhood n,
936 double max_cost,
937 std::ptrdiff_t bucket_count = 256)
938 {
939 vigra_precondition(src.shape() == dest.shape(),
940 "fastSeededRegionGrowing(): shape mismatch between input and output.");
941 return fastSeededRegionGrowing(srcImageRange(src),
942 destImage(dest),
943 stats, srgType, n, max_cost, bucket_count);
944 }
945
946 /********************************************************/
947 /* */
948 /* SeedRgDirectValueFunctor */
949 /* */
950 /********************************************************/
951
952 /** \brief Statistics functor to be used for seeded region growing.
953
954 This functor can be used if the cost of a candidate during
955 \ref seededRegionGrowing() is equal to the feature value of that
956 candidate and does not depend on properties of the region it is going to
957 be merged with.
958
959 <b>\#include</b> <vigra/seededregiongrowing.hxx><br>
960 Namespace: vigra
961 */
962 template <class Value>
963 class SeedRgDirectValueFunctor
964 {
965 public:
966 /** the functor's argument type
967 */
968 typedef Value argument_type;
969
970 /** the functor's result type (unused, only necessary for
971 use of SeedRgDirectValueFunctor in \ref vigra::ArrayOfRegionStatistics
972 */
973 typedef Value result_type;
974
975 /** \deprecated use argument_type
976 */
977 typedef Value value_type;
978
979 /** the return type of the cost() function
980 */
981 typedef Value cost_type;
982
983 /** Do nothing (since we need not update region statistics).
984 */
985 void operator()(argument_type const &) const {}
986
987 /** Return argument (since cost is identical to feature value)
988 */
989 cost_type const & cost(argument_type const & v) const
990 {
991 return v;
992 }
993 };
994
995 //@}
996
997 } // namespace vigra
998
999 #endif // VIGRA_SEEDEDREGIONGROWING_HXX
1000

© 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)