Point Cloud Library (PCL)  1.12.0-dev
region_growing_rgb.hpp
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39 
40 #ifndef PCL_SEGMENTATION_REGION_GROWING_RGB_HPP_
41 #define PCL_SEGMENTATION_REGION_GROWING_RGB_HPP_
42 
43 #include <pcl/console/print.h> // for PCL_ERROR
44 #include <pcl/segmentation/region_growing_rgb.h>
45 #include <pcl/search/search.h>
46 #include <pcl/search/kdtree.h>
47 
48 #include <queue>
49 
50 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
51 template <typename PointT, typename NormalT>
53  color_p2p_threshold_ (1225.0f),
54  color_r2r_threshold_ (10.0f),
55  distance_threshold_ (0.05f),
56  region_neighbour_number_ (100),
57  point_distances_ (0),
58  segment_neighbours_ (0),
59  segment_distances_ (0),
60  segment_labels_ (0)
61 {
62  normal_flag_ = false;
63  curvature_flag_ = false;
64  residual_flag_ = false;
66 }
67 
68 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
69 template <typename PointT, typename NormalT>
71 {
72  point_distances_.clear ();
73  segment_neighbours_.clear ();
74  segment_distances_.clear ();
75  segment_labels_.clear ();
76 }
77 
78 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
79 template <typename PointT, typename NormalT> float
81 {
82  return (powf (color_p2p_threshold_, 0.5f));
83 }
84 
85 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
86 template <typename PointT, typename NormalT> void
88 {
89  color_p2p_threshold_ = thresh * thresh;
90 }
91 
92 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
93 template <typename PointT, typename NormalT> float
95 {
96  return (powf (color_r2r_threshold_, 0.5f));
97 }
98 
99 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
100 template <typename PointT, typename NormalT> void
102 {
103  color_r2r_threshold_ = thresh * thresh;
104 }
105 
106 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
107 template <typename PointT, typename NormalT> float
109 {
110  return (powf (distance_threshold_, 0.5f));
111 }
112 
113 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
114 template <typename PointT, typename NormalT> void
116 {
117  distance_threshold_ = thresh * thresh;
118 }
119 
120 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
121 template <typename PointT, typename NormalT> unsigned int
123 {
124  return (region_neighbour_number_);
125 }
126 
127 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
128 template <typename PointT, typename NormalT> void
130 {
131  region_neighbour_number_ = nghbr_number;
132 }
133 
134 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
135 template <typename PointT, typename NormalT> bool
137 {
138  return (normal_flag_);
139 }
140 
141 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
142 template <typename PointT, typename NormalT> void
144 {
145  normal_flag_ = value;
146 }
147 
148 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
149 template <typename PointT, typename NormalT> void
151 {
152  curvature_flag_ = value;
153 }
154 
155 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
156 template <typename PointT, typename NormalT> void
158 {
159  residual_flag_ = value;
160 }
161 
162 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
163 template <typename PointT, typename NormalT> void
164 pcl::RegionGrowingRGB<PointT, NormalT>::extract (std::vector <pcl::PointIndices>& clusters)
165 {
166  clusters_.clear ();
167  clusters.clear ();
168  point_neighbours_.clear ();
169  point_labels_.clear ();
170  num_pts_in_segment_.clear ();
171  point_distances_.clear ();
172  segment_neighbours_.clear ();
173  segment_distances_.clear ();
174  segment_labels_.clear ();
175  number_of_segments_ = 0;
176 
177  bool segmentation_is_possible = initCompute ();
178  if ( !segmentation_is_possible )
179  {
180  deinitCompute ();
181  return;
182  }
183 
184  segmentation_is_possible = prepareForSegmentation ();
185  if ( !segmentation_is_possible )
186  {
187  deinitCompute ();
188  return;
189  }
190 
191  findPointNeighbours ();
192  applySmoothRegionGrowingAlgorithm ();
194 
195  findSegmentNeighbours ();
196  applyRegionMergingAlgorithm ();
197 
198  std::vector<pcl::PointIndices>::iterator cluster_iter = clusters_.begin ();
199  while (cluster_iter != clusters_.end ())
200  {
201  if (cluster_iter->indices.size () < min_pts_per_cluster_ ||
202  cluster_iter->indices.size () > max_pts_per_cluster_)
203  {
204  cluster_iter = clusters_.erase (cluster_iter);
205  }
206  else
207  ++cluster_iter;
208  }
209 
210  clusters.reserve (clusters_.size ());
211  std::copy (clusters_.begin (), clusters_.end (), std::back_inserter (clusters));
212 
213  deinitCompute ();
214 }
215 
216 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
217 template <typename PointT, typename NormalT> bool
219 {
220  // if user forgot to pass point cloud or if it is empty
221  if ( input_->points.empty () )
222  return (false);
223 
224  // if normal/smoothness test is on then we need to check if all needed variables and parameters
225  // were correctly initialized
226  if (normal_flag_)
227  {
228  // if user forgot to pass normals or the sizes of point and normal cloud are different
229  if ( !normals_ || input_->size () != normals_->size () )
230  return (false);
231  }
232 
233  // if residual test is on then we need to check if all needed parameters were correctly initialized
234  if (residual_flag_)
235  {
236  if (residual_threshold_ <= 0.0f)
237  return (false);
238  }
239 
240  // if curvature test is on ...
241  // if (curvature_flag_)
242  // {
243  // in this case we do not need to check anything that related to it
244  // so we simply commented it
245  // }
246 
247  // here we check the parameters related to color-based segmentation
248  if ( region_neighbour_number_ == 0 || color_p2p_threshold_ < 0.0f || color_r2r_threshold_ < 0.0f || distance_threshold_ < 0.0f )
249  return (false);
250 
251  // from here we check those parameters that are always valuable
252  if (neighbour_number_ == 0)
253  return (false);
254 
255  // if user didn't set search method
256  if (!search_)
257  search_.reset (new pcl::search::KdTree<PointT>);
258 
259  if (indices_)
260  {
261  if (indices_->empty ())
262  PCL_ERROR ("[pcl::RegionGrowingRGB::prepareForSegmentation] Empty given indices!\n");
263  search_->setInputCloud (input_, indices_);
264  }
265  else
266  search_->setInputCloud (input_);
267 
268  return (true);
269 }
270 
271 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
272 template <typename PointT, typename NormalT> void
274 {
275  int point_number = static_cast<int> (indices_->size ());
276  pcl::Indices neighbours;
277  std::vector<float> distances;
278 
279  point_neighbours_.resize (input_->size (), neighbours);
280  point_distances_.resize (input_->size (), distances);
281 
282  for (int i_point = 0; i_point < point_number; i_point++)
283  {
284  int point_index = (*indices_)[i_point];
285  neighbours.clear ();
286  distances.clear ();
287  search_->nearestKSearch (i_point, region_neighbour_number_, neighbours, distances);
288  point_neighbours_[point_index].swap (neighbours);
289  point_distances_[point_index].swap (distances);
290  }
291 }
292 
293 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
294 template <typename PointT, typename NormalT> void
296 {
297  pcl::Indices neighbours;
298  std::vector<float> distances;
299  segment_neighbours_.resize (number_of_segments_, neighbours);
300  segment_distances_.resize (number_of_segments_, distances);
301 
302  for (int i_seg = 0; i_seg < number_of_segments_; i_seg++)
303  {
304  pcl::Indices nghbrs;
305  std::vector<float> dist;
306  findRegionsKNN (i_seg, region_neighbour_number_, nghbrs, dist);
307  segment_neighbours_[i_seg].swap (nghbrs);
308  segment_distances_[i_seg].swap (dist);
309  }
310 }
311 
312 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
313 template <typename PointT,typename NormalT> void
315 {
316  std::vector<float> distances;
317  float max_dist = std::numeric_limits<float>::max ();
318  distances.resize (clusters_.size (), max_dist);
319 
320  const auto number_of_points = num_pts_in_segment_[index];
321  //loop through every point in this segment and check neighbours
322  for (pcl::uindex_t i_point = 0; i_point < number_of_points; i_point++)
323  {
324  const auto point_index = clusters_[index].indices[i_point];
325  const auto number_of_neighbours = point_neighbours_[point_index].size ();
326  //loop through every neighbour of the current point, find out to which segment it belongs
327  //and if it belongs to neighbouring segment and is close enough then remember segment and its distance
328  for (std::size_t i_nghbr = 0; i_nghbr < number_of_neighbours; i_nghbr++)
329  {
330  // find segment
331  const pcl::index_t segment_index = point_labels_[ point_neighbours_[point_index][i_nghbr] ];
332 
333  if ( segment_index != index )
334  {
335  // try to push it to the queue
336  if (distances[segment_index] > point_distances_[point_index][i_nghbr])
337  distances[segment_index] = point_distances_[point_index][i_nghbr];
338  }
339  }
340  }// next point
341 
342  std::priority_queue<std::pair<float, int> > segment_neighbours;
343  for (int i_seg = 0; i_seg < number_of_segments_; i_seg++)
344  {
345  if (distances[i_seg] < max_dist)
346  {
347  segment_neighbours.push (std::make_pair (distances[i_seg], i_seg) );
348  if (segment_neighbours.size () > nghbr_number)
349  segment_neighbours.pop ();
350  }
351  }
352 
353  const std::size_t size = std::min<std::size_t> (segment_neighbours.size (), static_cast<std::size_t>(nghbr_number));
354  nghbrs.resize (size, 0);
355  dist.resize (size, 0);
356  pcl::uindex_t counter = 0;
357  while ( !segment_neighbours.empty () && counter < nghbr_number )
358  {
359  dist[counter] = segment_neighbours.top ().first;
360  nghbrs[counter] = segment_neighbours.top ().second;
361  segment_neighbours.pop ();
362  counter++;
363  }
364 }
365 
366 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
367 template <typename PointT, typename NormalT> void
369 {
370  // calculate color of each segment
371  std::vector< std::vector<unsigned int> > segment_color;
372  std::vector<unsigned int> color;
373  color.resize (3, 0);
374  segment_color.resize (number_of_segments_, color);
375 
376  for (const auto& point_index : (*indices_))
377  {
378  int segment_index = point_labels_[point_index];
379  segment_color[segment_index][0] += (*input_)[point_index].r;
380  segment_color[segment_index][1] += (*input_)[point_index].g;
381  segment_color[segment_index][2] += (*input_)[point_index].b;
382  }
383  for (int i_seg = 0; i_seg < number_of_segments_; i_seg++)
384  {
385  segment_color[i_seg][0] = static_cast<unsigned int> (static_cast<float> (segment_color[i_seg][0]) / static_cast<float> (num_pts_in_segment_[i_seg]));
386  segment_color[i_seg][1] = static_cast<unsigned int> (static_cast<float> (segment_color[i_seg][1]) / static_cast<float> (num_pts_in_segment_[i_seg]));
387  segment_color[i_seg][2] = static_cast<unsigned int> (static_cast<float> (segment_color[i_seg][2]) / static_cast<float> (num_pts_in_segment_[i_seg]));
388  }
389 
390  // now it is time to find out if there are segments with a similar color
391  // and merge them together
392  std::vector<unsigned int> num_pts_in_homogeneous_region;
393  std::vector<int> num_seg_in_homogeneous_region;
394 
395  segment_labels_.resize (number_of_segments_, -1);
396 
397  float dist_thresh = distance_threshold_;
398  int homogeneous_region_number = 0;
399  for (int i_seg = 0; i_seg < number_of_segments_; i_seg++)
400  {
401  int curr_homogeneous_region = 0;
402  if (segment_labels_[i_seg] == -1)
403  {
404  segment_labels_[i_seg] = homogeneous_region_number;
405  curr_homogeneous_region = homogeneous_region_number;
406  num_pts_in_homogeneous_region.push_back (num_pts_in_segment_[i_seg]);
407  num_seg_in_homogeneous_region.push_back (1);
408  homogeneous_region_number++;
409  }
410  else
411  curr_homogeneous_region = segment_labels_[i_seg];
412 
413  unsigned int i_nghbr = 0;
414  while ( i_nghbr < region_neighbour_number_ && i_nghbr < segment_neighbours_[i_seg].size () )
415  {
416  int index = segment_neighbours_[i_seg][i_nghbr];
417  if (segment_distances_[i_seg][i_nghbr] > dist_thresh)
418  {
419  i_nghbr++;
420  continue;
421  }
422  if ( segment_labels_[index] == -1 )
423  {
424  float difference = calculateColorimetricalDifference (segment_color[i_seg], segment_color[index]);
425  if (difference < color_r2r_threshold_)
426  {
427  segment_labels_[index] = curr_homogeneous_region;
428  num_pts_in_homogeneous_region[curr_homogeneous_region] += num_pts_in_segment_[index];
429  num_seg_in_homogeneous_region[curr_homogeneous_region] += 1;
430  }
431  }
432  i_nghbr++;
433  }// next neighbour
434  }// next segment
435 
436  segment_color.clear ();
437  color.clear ();
438 
439  std::vector< std::vector<int> > final_segments;
440  std::vector<int> region;
441  final_segments.resize (homogeneous_region_number, region);
442  for (int i_reg = 0; i_reg < homogeneous_region_number; i_reg++)
443  {
444  final_segments[i_reg].resize (num_seg_in_homogeneous_region[i_reg], 0);
445  }
446 
447  std::vector<int> counter;
448  counter.resize (homogeneous_region_number, 0);
449  for (int i_seg = 0; i_seg < number_of_segments_; i_seg++)
450  {
451  int index = segment_labels_[i_seg];
452  final_segments[ index ][ counter[index] ] = i_seg;
453  counter[index] += 1;
454  }
455 
456  std::vector< std::vector< std::pair<float, pcl::index_t> > > region_neighbours;
457  findRegionNeighbours (region_neighbours, final_segments);
458 
459  int final_segment_number = homogeneous_region_number;
460  for (int i_reg = 0; i_reg < homogeneous_region_number; i_reg++)
461  {
462  if (num_pts_in_homogeneous_region[i_reg] < min_pts_per_cluster_)
463  {
464  if ( region_neighbours[i_reg].empty () )
465  continue;
466  int nearest_neighbour = region_neighbours[i_reg][0].second;
467  if ( region_neighbours[i_reg][0].first == std::numeric_limits<float>::max () )
468  continue;
469  int reg_index = segment_labels_[nearest_neighbour];
470  int num_seg_in_reg = num_seg_in_homogeneous_region[i_reg];
471  for (int i_seg = 0; i_seg < num_seg_in_reg; i_seg++)
472  {
473  int segment_index = final_segments[i_reg][i_seg];
474  final_segments[reg_index].push_back (segment_index);
475  segment_labels_[segment_index] = reg_index;
476  }
477  final_segments[i_reg].clear ();
478  num_pts_in_homogeneous_region[reg_index] += num_pts_in_homogeneous_region[i_reg];
479  num_pts_in_homogeneous_region[i_reg] = 0;
480  num_seg_in_homogeneous_region[reg_index] += num_seg_in_homogeneous_region[i_reg];
481  num_seg_in_homogeneous_region[i_reg] = 0;
482  final_segment_number -= 1;
483 
484  for (auto& nghbr : region_neighbours[reg_index])
485  {
486  if ( segment_labels_[ nghbr.second ] == reg_index )
487  {
488  nghbr.first = std::numeric_limits<float>::max ();
489  nghbr.second = 0;
490  }
491  }
492  for (const auto& nghbr : region_neighbours[i_reg])
493  {
494  if ( segment_labels_[ nghbr.second ] != reg_index )
495  {
496  region_neighbours[reg_index].push_back (nghbr);
497  }
498  }
499  region_neighbours[i_reg].clear ();
500  std::sort (region_neighbours[reg_index].begin (), region_neighbours[reg_index].end (), comparePair);
501  }
502  }
503 
504  assembleRegions (num_pts_in_homogeneous_region, static_cast<int> (num_pts_in_homogeneous_region.size ()));
505 
506  number_of_segments_ = final_segment_number;
507 }
508 
509 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
510 template <typename PointT, typename NormalT> float
511 pcl::RegionGrowingRGB<PointT, NormalT>::calculateColorimetricalDifference (std::vector<unsigned int>& first_color, std::vector<unsigned int>& second_color) const
512 {
513  float difference = 0.0f;
514  difference += float ((first_color[0] - second_color[0]) * (first_color[0] - second_color[0]));
515  difference += float ((first_color[1] - second_color[1]) * (first_color[1] - second_color[1]));
516  difference += float ((first_color[2] - second_color[2]) * (first_color[2] - second_color[2]));
517  return (difference);
518 }
519 
520 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
521 template <typename PointT, typename NormalT> void
522 pcl::RegionGrowingRGB<PointT, NormalT>::findRegionNeighbours (std::vector< std::vector< std::pair<float, pcl::index_t> > >& neighbours_out, std::vector< std::vector<int> >& regions_in)
523 {
524  int region_number = static_cast<int> (regions_in.size ());
525  neighbours_out.clear ();
526  neighbours_out.resize (region_number);
527 
528  for (int i_reg = 0; i_reg < region_number; i_reg++)
529  {
530  neighbours_out[i_reg].reserve (regions_in[i_reg].size () * region_neighbour_number_);
531  for (const auto& curr_segment : regions_in[i_reg])
532  {
533  const std::size_t nghbr_number = segment_neighbours_[curr_segment].size ();
534  std::pair<float, pcl::index_t> pair;
535  for (std::size_t i_nghbr = 0; i_nghbr < nghbr_number; i_nghbr++)
536  {
537  const auto segment_index = segment_neighbours_[curr_segment][i_nghbr];
538  if ( segment_distances_[curr_segment][i_nghbr] == std::numeric_limits<float>::max () )
539  continue;
540  if (segment_labels_[segment_index] != i_reg)
541  {
542  pair.first = segment_distances_[curr_segment][i_nghbr];
543  pair.second = segment_index;
544  neighbours_out[i_reg].push_back (pair);
545  }
546  }// next neighbour
547  }// next segment
548  std::sort (neighbours_out[i_reg].begin (), neighbours_out[i_reg].end (), comparePair);
549  }// next homogeneous region
550 }
551 
552 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
553 template <typename PointT, typename NormalT> void
554 pcl::RegionGrowingRGB<PointT, NormalT>::assembleRegions (std::vector<unsigned int>& num_pts_in_region, int num_regions)
555 {
556  clusters_.clear ();
557  pcl::PointIndices segment;
558  clusters_.resize (num_regions, segment);
559  for (int i_seg = 0; i_seg < num_regions; i_seg++)
560  {
561  clusters_[i_seg].indices.resize (num_pts_in_region[i_seg]);
562  }
563 
564  std::vector<int> counter;
565  counter.resize (num_regions, 0);
566  for (const auto& point_index : (*indices_))
567  {
568  int index = point_labels_[point_index];
569  index = segment_labels_[index];
570  clusters_[index].indices[ counter[index] ] = point_index;
571  counter[index] += 1;
572  }
573 
574  // now we need to erase empty regions
575  if (clusters_.empty ())
576  return;
577 
578  std::vector<pcl::PointIndices>::iterator itr1, itr2;
579  itr1 = clusters_.begin ();
580  itr2 = clusters_.end () - 1;
581 
582  while (itr1 < itr2)
583  {
584  while (!(itr1->indices.empty ()) && itr1 < itr2)
585  ++itr1;
586  while ( itr2->indices.empty () && itr1 < itr2)
587  --itr2;
588 
589  if (itr1 != itr2)
590  itr1->indices.swap (itr2->indices);
591  }
592 
593  if (itr2->indices.empty ())
594  clusters_.erase (itr2, clusters_.end ());
595 }
596 
597 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
598 template <typename PointT, typename NormalT> bool
600 {
601  is_a_seed = true;
602 
603  // check the color difference
604  std::vector<unsigned int> point_color;
605  point_color.resize (3, 0);
606  std::vector<unsigned int> nghbr_color;
607  nghbr_color.resize (3, 0);
608  point_color[0] = (*input_)[point].r;
609  point_color[1] = (*input_)[point].g;
610  point_color[2] = (*input_)[point].b;
611  nghbr_color[0] = (*input_)[nghbr].r;
612  nghbr_color[1] = (*input_)[nghbr].g;
613  nghbr_color[2] = (*input_)[nghbr].b;
614  float difference = calculateColorimetricalDifference (point_color, nghbr_color);
615  if (difference > color_p2p_threshold_)
616  return (false);
617 
618  float cosine_threshold = std::cos (theta_threshold_);
619 
620  // check the angle between normals if needed
621  if (normal_flag_)
622  {
623  float data[4];
624  data[0] = (*input_)[point].data[0];
625  data[1] = (*input_)[point].data[1];
626  data[2] = (*input_)[point].data[2];
627  data[3] = (*input_)[point].data[3];
628 
629  Eigen::Map<Eigen::Vector3f> initial_point (static_cast<float*> (data));
630  Eigen::Map<Eigen::Vector3f> initial_normal (static_cast<float*> ((*normals_)[point].normal));
631  if (smooth_mode_flag_ == true)
632  {
633  Eigen::Map<Eigen::Vector3f> nghbr_normal (static_cast<float*> ((*normals_)[nghbr].normal));
634  float dot_product = std::abs (nghbr_normal.dot (initial_normal));
635  if (dot_product < cosine_threshold)
636  return (false);
637  }
638  else
639  {
640  Eigen::Map<Eigen::Vector3f> nghbr_normal (static_cast<float*> ((*normals_)[nghbr].normal));
641  Eigen::Map<Eigen::Vector3f> initial_seed_normal (static_cast<float*> ((*normals_)[initial_seed].normal));
642  float dot_product = std::abs (nghbr_normal.dot (initial_seed_normal));
643  if (dot_product < cosine_threshold)
644  return (false);
645  }
646  }
647 
648  // check the curvature if needed
649  if (curvature_flag_ && (*normals_)[nghbr].curvature > curvature_threshold_)
650  is_a_seed = false;
651 
652  // check the residual if needed
653  if (residual_flag_)
654  {
655  float data_p[4];
656  data_p[0] = (*input_)[point].data[0];
657  data_p[1] = (*input_)[point].data[1];
658  data_p[2] = (*input_)[point].data[2];
659  data_p[3] = (*input_)[point].data[3];
660  float data_n[4];
661  data_n[0] = (*input_)[nghbr].data[0];
662  data_n[1] = (*input_)[nghbr].data[1];
663  data_n[2] = (*input_)[nghbr].data[2];
664  data_n[3] = (*input_)[nghbr].data[3];
665  Eigen::Map<Eigen::Vector3f> nghbr_point (static_cast<float*> (data_n));
666  Eigen::Map<Eigen::Vector3f> initial_point (static_cast<float*> (data_p));
667  Eigen::Map<Eigen::Vector3f> initial_normal (static_cast<float*> ((*normals_)[point].normal));
668  float residual = std::abs (initial_normal.dot (initial_point - nghbr_point));
669  if (residual > residual_threshold_)
670  is_a_seed = false;
671  }
672 
673  return (true);
674 }
675 
676 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
677 template <typename PointT, typename NormalT> void
679 {
680  cluster.indices.clear ();
681 
682  bool segmentation_is_possible = initCompute ();
683  if ( !segmentation_is_possible )
684  {
685  deinitCompute ();
686  return;
687  }
688 
689  // first of all we need to find out if this point belongs to cloud
690  bool point_was_found = false;
691  for (const auto& point : (*indices_))
692  if (point == index)
693  {
694  point_was_found = true;
695  break;
696  }
697 
698  if (point_was_found)
699  {
700  if (clusters_.empty ())
701  {
702  clusters_.clear ();
703  point_neighbours_.clear ();
704  point_labels_.clear ();
705  num_pts_in_segment_.clear ();
706  point_distances_.clear ();
707  segment_neighbours_.clear ();
708  segment_distances_.clear ();
709  segment_labels_.clear ();
710  number_of_segments_ = 0;
711 
712  segmentation_is_possible = prepareForSegmentation ();
713  if ( !segmentation_is_possible )
714  {
715  deinitCompute ();
716  return;
717  }
718 
719  findPointNeighbours ();
720  applySmoothRegionGrowingAlgorithm ();
722 
723  findSegmentNeighbours ();
724  applyRegionMergingAlgorithm ();
725  }
726  // if we have already made the segmentation, then find the segment
727  // to which this point belongs
728  for (const auto& i_segment : clusters_)
729  {
730  const auto it = std::find (i_segment.indices.cbegin (), i_segment.indices.cend (), index);
731  if (it != i_segment.indices.cend())
732  {
733  // if segment was found
734  cluster.indices.clear ();
735  cluster.indices.reserve (i_segment.indices.size ());
736  std::copy (i_segment.indices.begin (), i_segment.indices.end (), std::back_inserter (cluster.indices));
737  break;
738  }
739  }// next segment
740  }// end if point was found
741 
742  deinitCompute ();
743 }
744 
745 #endif // PCL_SEGMENTATION_REGION_GROWING_RGB_HPP_
pcl::RegionGrowing< PointT, pcl::Normal >::min_pts_per_cluster_
pcl::uindex_t min_pts_per_cluster_
Stores the minimum number of points that a cluster needs to contain in order to be considered valid.
Definition: region_growing.h:282
pcl::RegionGrowingRGB::getRegionColorThreshold
float getRegionColorThreshold() const
Returns the color threshold value used for testing if regions can be merged.
Definition: region_growing_rgb.hpp:94
pcl::RegionGrowingRGB::setNormalTestFlag
void setNormalTestFlag(bool value)
Allows to turn on/off the smoothness test.
Definition: region_growing_rgb.hpp:143
pcl::RegionGrowingRGB::getNormalTestFlag
bool getNormalTestFlag() const
Returns the flag that signalize if the smoothness test is turned on/off.
Definition: region_growing_rgb.hpp:136
pcl::RegionGrowing< PointT, pcl::Normal >::normal_flag_
bool normal_flag_
If set to true then normal/smoothness test will be done during segmentation.
Definition: region_growing.h:323
pcl::RegionGrowingRGB::findPointNeighbours
void findPointNeighbours() override
This method finds KNN for each point and saves them to the array because the algorithm needs to find ...
Definition: region_growing_rgb.hpp:273
pcl::RegionGrowingRGB::getNumberOfRegionNeighbours
unsigned int getNumberOfRegionNeighbours() const
Returns the number of nearest neighbours used for searching K nearest segments.
Definition: region_growing_rgb.hpp:122
pcl::RegionGrowing< PointT, pcl::Normal >::curvature_flag_
bool curvature_flag_
If set to true then curvature test will be done during segmentation.
Definition: region_growing.h:291
pcl::RegionGrowingRGB::setCurvatureTestFlag
void setCurvatureTestFlag(bool value) override
Allows to turn on/off the curvature test.
Definition: region_growing_rgb.hpp:150
pcl::RegionGrowingRGB::getSegmentFromPoint
void getSegmentFromPoint(index_t index, pcl::PointIndices &cluster) override
For a given point this function builds a segment to which it belongs and returns this segment.
Definition: region_growing_rgb.hpp:678
pcl::RegionGrowingRGB::setPointColorThreshold
void setPointColorThreshold(float thresh)
This method specifies the threshold value for color test between the points.
Definition: region_growing_rgb.hpp:87
pcl::PointIndices::indices
Indices indices
Definition: PointIndices.h:21
pcl::RegionGrowingRGB::extract
void extract(std::vector< pcl::PointIndices > &clusters) override
This method launches the segmentation algorithm and returns the clusters that were obtained during th...
Definition: region_growing_rgb.hpp:164
pcl::index_t
detail::int_type_t< detail::index_type_size, detail::index_type_signed > index_t
Type used for an index in PCL.
Definition: types.h:112
pcl::RegionGrowingRGB::calculateColorimetricalDifference
float calculateColorimetricalDifference(std::vector< unsigned int > &first_color, std::vector< unsigned int > &second_color) const
This method calculates the colorimetrical difference between two points.
Definition: region_growing_rgb.hpp:511
pcl::RegionGrowing< PointT, pcl::Normal >::residual_flag_
bool residual_flag_
If set to true then residual test will be done during segmentation.
Definition: region_growing.h:294
pcl::RegionGrowingRGB::findRegionsKNN
void findRegionsKNN(pcl::index_t index, pcl::uindex_t nghbr_number, Indices &nghbrs, std::vector< float > &dist)
This method finds K nearest neighbours of the given segment.
Definition: region_growing_rgb.hpp:314
pcl::RegionGrowingRGB::setResidualTestFlag
void setResidualTestFlag(bool value) override
Allows to turn on/off the residual test.
Definition: region_growing_rgb.hpp:157
pcl::RegionGrowingRGB::~RegionGrowingRGB
~RegionGrowingRGB()
Destructor that frees memory.
Definition: region_growing_rgb.hpp:70
pcl::RegionGrowingRGB::prepareForSegmentation
bool prepareForSegmentation() override
This method simply checks if it is possible to execute the segmentation algorithm with the current se...
Definition: region_growing_rgb.hpp:218
pcl::comparePair
bool comparePair(std::pair< float, int > i, std::pair< float, int > j)
This function is used as a comparator for sorting.
Definition: region_growing.h:340
pcl::search::KdTree< PointT >
pcl::RegionGrowing::assembleRegions
void assembleRegions()
This function simply assembles the regions from list of point labels.
Definition: region_growing.hpp:539
pcl::RegionGrowingRGB::findSegmentNeighbours
void findSegmentNeighbours()
This method simply calls the findRegionsKNN for each segment and saves the results for later use.
Definition: region_growing_rgb.hpp:295
pcl::RegionGrowingRGB::setNumberOfRegionNeighbours
void setNumberOfRegionNeighbours(unsigned int nghbr_number)
This method allows to set the number of neighbours that is used for finding neighbouring segments.
Definition: region_growing_rgb.hpp:129
pcl::RegionGrowingRGB::setDistanceThreshold
void setDistanceThreshold(float thresh)
Allows to set distance threshold.
Definition: region_growing_rgb.hpp:115
pcl::PointIndices
Definition: PointIndices.h:11
pcl::RegionGrowingRGB::findRegionNeighbours
void findRegionNeighbours(std::vector< std::vector< std::pair< float, pcl::index_t > > > &neighbours_out, std::vector< std::vector< int > > &regions_in)
This method assembles the array containing neighbours of each homogeneous region.
Definition: region_growing_rgb.hpp:522
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
pcl::RegionGrowingRGB::setRegionColorThreshold
void setRegionColorThreshold(float thresh)
This method specifies the threshold value for color test between the regions.
Definition: region_growing_rgb.hpp:101
pcl::RegionGrowingRGB::getPointColorThreshold
float getPointColorThreshold() const
Returns the color threshold value used for testing if points belong to the same region.
Definition: region_growing_rgb.hpp:80
pcl::RegionGrowingRGB::validatePoint
bool validatePoint(index_t initial_seed, index_t point, index_t nghbr, bool &is_a_seed) const override
This function is checking if the point with index 'nghbr' belongs to the segment.
Definition: region_growing_rgb.hpp:599
pcl::RegionGrowingRGB::RegionGrowingRGB
RegionGrowingRGB()
Constructor that sets default values for member variables.
Definition: region_growing_rgb.hpp:52
pcl::RegionGrowingRGB::applyRegionMergingAlgorithm
void applyRegionMergingAlgorithm()
This function implements the merging algorithm described in the article "Color-based segmentation of ...
Definition: region_growing_rgb.hpp:368
pcl::RegionGrowingRGB::getDistanceThreshold
float getDistanceThreshold() const
Returns the distance threshold.
Definition: region_growing_rgb.hpp:108
pcl::uindex_t
detail::int_type_t< detail::index_type_size, false > uindex_t
Type used for an unsigned index in PCL.
Definition: types.h:120