Point Cloud Library (PCL) 1.12.0
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organized_edge_detection.h
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37
38#pragma once
39
40#include <pcl/pcl_base.h>
41#include <pcl/PointIndices.h>
42
43namespace pcl
44{
45 /** \brief OrganizedEdgeBase, OrganizedEdgeFromRGB, OrganizedEdgeFromNormals,
46 * and OrganizedEdgeFromRGBNormals find 3D edges from an organized point
47 * cloud data. Given an organized point cloud, they will output a PointCloud
48 * of edge labels and a vector of PointIndices.
49 * OrganizedEdgeBase accepts PCL_XYZ_POINT_TYPES and returns EDGELABEL_NAN_BOUNDARY, EDGELABEL_OCCLUDING, and EDGELABEL_OCCLUDED.
50 * OrganizedEdgeFromRGB accepts PCL_RGB_POINT_TYPES and returns EDGELABEL_NAN_BOUNDARY, EDGELABEL_OCCLUDING, EDGELABEL_OCCLUDED, and EDGELABEL_RGB_CANNY.
51 * OrganizedEdgeFromNormals accepts PCL_XYZ_POINT_TYPES with PCL_NORMAL_POINT_TYPES and returns EDGELABEL_NAN_BOUNDARY, EDGELABEL_OCCLUDING, EDGELABEL_OCCLUDED, and EDGELABEL_HIGH_CURVATURE.
52 * OrganizedEdgeFromRGBNormals accepts PCL_RGB_POINT_TYPES with PCL_NORMAL_POINT_TYPES and returns EDGELABEL_NAN_BOUNDARY, EDGELABEL_OCCLUDING, EDGELABEL_OCCLUDED, EDGELABEL_HIGH_CURVATURE, and EDGELABEL_RGB_CANNY.
53 *
54 * \author Changhyun Choi
55 */
56 template <typename PointT, typename PointLT>
57 class OrganizedEdgeBase : public PCLBase<PointT>
58 {
60 using PointCloudPtr = typename PointCloud::Ptr;
61 using PointCloudConstPtr = typename PointCloud::ConstPtr;
62
64 using PointCloudLPtr = typename PointCloudL::Ptr;
65 using PointCloudLConstPtr = typename PointCloudL::ConstPtr;
66
67 public:
68 using Ptr = shared_ptr<OrganizedEdgeBase<PointT, PointLT> >;
69 using ConstPtr = shared_ptr<const OrganizedEdgeBase<PointT, PointLT> >;
74
75 /** \brief Constructor for OrganizedEdgeBase */
82
83 /** \brief Destructor for OrganizedEdgeBase */
84
86 {
87 }
88
89 /** \brief Perform the 3D edge detection (edges from depth discontinuities)
90 * \param[out] labels a PointCloud of edge labels
91 * \param[out] label_indices a vector of PointIndices corresponding to each edge label
92 */
93 void
94 compute (pcl::PointCloud<PointLT>& labels, std::vector<pcl::PointIndices>& label_indices) const;
95
96 /** \brief Set the tolerance in meters for the relative difference in depth values between neighboring points.
97 * e.g. If a point has a depth (z) value of 2.0 meters, a neighboring point is discontinuous if its depth differs by > 2.0 * th. */
98 inline void
99 setDepthDisconThreshold (const float th)
100 {
101 th_depth_discon_ = th;
102 }
103
104 /** \brief Get the tolerance in meters for the relative difference in depth values between neighboring points.
105 * e.g. If a point has a depth (z) value of 2.0 meters, a neighboring point is discontinuous if its depth differs by > 2.0 * th. */
106 inline float
108 {
109 return (th_depth_discon_);
110 }
111
112 /** \brief Set the max search distance for deciding occluding and occluded edges. */
113 inline void
114 setMaxSearchNeighbors (const int max_dist)
115 {
116 max_search_neighbors_ = max_dist;
117 }
118
119 /** \brief Get the max search distance for deciding occluding and occluded edges. */
120 inline int
122 {
123 return (max_search_neighbors_);
124 }
125
126 /** \brief Set the detecting edge types. */
127 inline void
128 setEdgeType (int edge_types)
129 {
130 detecting_edge_types_ = edge_types;
131 }
132
133 /** \brief Get the detecting edge types. */
134 inline int
135 getEdgeType () const
136 {
138 }
139
141 static const int num_of_edgetype_ = 5;
142
143 protected:
144 /** \brief Perform the 3D edge detection (edges from depth discontinuities) and assign point indices for each edge label
145 * \param[out] labels a PointCloud of edge labels
146 */
147 void
149
150 /** \brief Assign point indices for each edge label
151 * \param[out] labels a PointCloud of edge labels
152 * \param[out] label_indices a vector of PointIndices corresponding to each edge label
153 */
154 void
155 assignLabelIndices (pcl::PointCloud<PointLT>& labels, std::vector<pcl::PointIndices>& label_indices) const;
156
157 struct Neighbor
158 {
159 Neighbor (int dx, int dy, int didx)
160 : d_x (dx)
161 , d_y (dy)
162 , d_index (didx)
163 {}
164
165 int d_x;
166 int d_y;
167 int d_index; // = dy * width + dx: pre-calculated
168 };
169
170 /** \brief The tolerance in meters for the relative difference in depth values between neighboring points
171 * (The default value is set for .02 meters and is adapted with respect to depth value linearly.
172 * e.g. If a point has a depth (z) value of 2.0 meters, a neighboring point is discontinuous if its depth differs by > 2.0 * th. */
174
175 /** \brief The max search distance for deciding occluding and occluded edges */
177
178 /** \brief The bit encoded value that represents edge types to detect */
180 };
181
182 template <typename PointT, typename PointLT>
183 class OrganizedEdgeFromRGB : virtual public OrganizedEdgeBase<PointT, PointLT>
184 {
186 using PointCloudPtr = typename PointCloud::Ptr;
187 using PointCloudConstPtr = typename PointCloud::ConstPtr;
188
190 using PointCloudLPtr = typename PointCloudL::Ptr;
191 using PointCloudLConstPtr = typename PointCloudL::ConstPtr;
192
193 public:
194 using OrganizedEdgeBase<PointT, PointLT>::input_;
195 using OrganizedEdgeBase<PointT, PointLT>::indices_;
203
204 /** \brief Constructor for OrganizedEdgeFromRGB */
212
213 /** \brief Destructor for OrganizedEdgeFromRGB */
214
216 {
217 }
218
219 /** \brief Perform the 3D edge detection (edges from depth discontinuities and RGB Canny edge) and assign point indices for each edge label
220 * \param[out] labels a PointCloud of edge labels
221 * \param[out] label_indices a vector of PointIndices corresponding to each edge label
222 */
223 void
224 compute (pcl::PointCloud<PointLT>& labels, std::vector<pcl::PointIndices>& label_indices) const;
225
226 /** \brief Set the low threshold value for RGB Canny edge detection */
227 inline void
228 setRGBCannyLowThreshold (const float th)
229 {
231 }
232
233 /** \brief Get the low threshold value for RGB Canny edge detection */
234 inline float
236 {
237 return (th_rgb_canny_low_);
238 }
239
240 /** \brief Set the high threshold value for RGB Canny edge detection */
241 inline void
243 {
245 }
246
247 /** \brief Get the high threshold value for RGB Canny edge detection */
248 inline float
250 {
251 return (th_rgb_canny_high_);
252 }
253
254 protected:
255 /** \brief Perform the 3D edge detection (edges from depth discontinuities and RGB Canny edge)
256 * \param[out] labels a PointCloud of edge labels
257 */
258 void
260
261 /** \brief The low threshold value for RGB Canny edge detection (default: 40.0) */
263
264 /** \brief The high threshold value for RGB Canny edge detection (default: 100.0) */
266 };
267
268 template <typename PointT, typename PointNT, typename PointLT>
269 class OrganizedEdgeFromNormals : virtual public OrganizedEdgeBase<PointT, PointLT>
270 {
272 using PointCloudPtr = typename PointCloud::Ptr;
273 using PointCloudConstPtr = typename PointCloud::ConstPtr;
274
276 using PointCloudNPtr = typename PointCloudN::Ptr;
277 using PointCloudNConstPtr = typename PointCloudN::ConstPtr;
278
280 using PointCloudLPtr = typename PointCloudL::Ptr;
281 using PointCloudLConstPtr = typename PointCloudL::ConstPtr;
282
283 public:
284 using OrganizedEdgeBase<PointT, PointLT>::input_;
285 using OrganizedEdgeBase<PointT, PointLT>::indices_;
293
294 /** \brief Constructor for OrganizedEdgeFromNormals */
303
304 /** \brief Destructor for OrganizedEdgeFromNormals */
305
309
310 /** \brief Perform the 3D edge detection (edges from depth discontinuities and high curvature regions) and assign point indices for each edge label
311 * \param[out] labels a PointCloud of edge labels
312 * \param[out] label_indices a vector of PointIndices corresponding to each edge label
313 */
314 void
315 compute (pcl::PointCloud<PointLT>& labels, std::vector<pcl::PointIndices>& label_indices) const;
316
317 /** \brief Provide a pointer to the input normals.
318 * \param[in] normals the input normal cloud
319 */
320 inline void
321 setInputNormals (const PointCloudNConstPtr &normals)
322 {
323 normals_ = normals;
324 }
325
326 /** \brief Get the input normals. */
327 inline PointCloudNConstPtr
329 {
330 return (normals_);
331 }
332
333 /** \brief Set the low threshold value for high curvature Canny edge detection */
334 inline void
335 setHCCannyLowThreshold (const float th)
336 {
337 th_hc_canny_low_ = th;
338 }
339
340 /** \brief Get the low threshold value for high curvature Canny edge detection */
341 inline float
343 {
344 return (th_hc_canny_low_);
345 }
346
347 /** \brief Set the high threshold value for high curvature Canny edge detection */
348 inline void
349 setHCCannyHighThreshold (const float th)
350 {
352 }
353
354 /** \brief Get the high threshold value for high curvature Canny edge detection */
355 inline float
357 {
358 return (th_hc_canny_high_);
359 }
360
361 protected:
362 /** \brief Perform the 3D edge detection (edges from depth discontinuities and high curvature regions)
363 * \param[out] labels a PointCloud of edge labels
364 */
365 void
367
368 /** \brief A pointer to the input normals */
369 PointCloudNConstPtr normals_;
370
371 /** \brief The low threshold value for high curvature Canny edge detection (default: 0.4) */
373
374 /** \brief The high threshold value for high curvature Canny edge detection (default: 1.1) */
376 };
377
378 template <typename PointT, typename PointNT, typename PointLT>
379 class OrganizedEdgeFromRGBNormals : public OrganizedEdgeFromRGB<PointT, PointLT>, public OrganizedEdgeFromNormals<PointT, PointNT, PointLT>
380 {
382 using PointCloudPtr = typename PointCloud::Ptr;
383 using PointCloudConstPtr = typename PointCloud::ConstPtr;
384
386 using PointCloudNPtr = typename PointCloudN::Ptr;
387 using PointCloudNConstPtr = typename PointCloudN::ConstPtr;
388
390 using PointCloudLPtr = typename PointCloudL::Ptr;
391 using PointCloudLConstPtr = typename PointCloudL::ConstPtr;
392
393 public:
394 using OrganizedEdgeFromNormals<PointT, PointNT, PointLT>::input_;
395 using OrganizedEdgeFromNormals<PointT, PointNT, PointLT>::indices_;
396 using OrganizedEdgeFromNormals<PointT, PointNT, PointLT>::initCompute;
397 using OrganizedEdgeFromNormals<PointT, PointNT, PointLT>::deinitCompute;
404
405 /** \brief Constructor for OrganizedEdgeFromRGBNormals */
412
413 /** \brief Destructor for OrganizedEdgeFromRGBNormals */
414
418
419 /** \brief Perform the 3D edge detection (edges from depth discontinuities, RGB Canny edge, and high curvature regions) and assign point indices for each edge label
420 * \param[out] labels a PointCloud of edge labels
421 * \param[out] label_indices a vector of PointIndices corresponding to each edge label
422 */
423 void
424 compute (pcl::PointCloud<PointLT>& labels, std::vector<pcl::PointIndices>& label_indices) const;
425 };
426}
427
428#ifdef PCL_NO_PRECOMPILE
429#include <pcl/features/impl/organized_edge_detection.hpp>
430#endif
OrganizedEdgeBase, OrganizedEdgeFromRGB, OrganizedEdgeFromNormals, and OrganizedEdgeFromRGBNormals fi...
int getEdgeType() const
Get the detecting edge types.
~OrganizedEdgeBase()
Destructor for OrganizedEdgeBase.
float th_depth_discon_
The tolerance in meters for the relative difference in depth values between neighboring points (The d...
int getMaxSearchNeighbors() const
Get the max search distance for deciding occluding and occluded edges.
int detecting_edge_types_
The bit encoded value that represents edge types to detect.
OrganizedEdgeBase()
Constructor for OrganizedEdgeBase.
void assignLabelIndices(pcl::PointCloud< PointLT > &labels, std::vector< pcl::PointIndices > &label_indices) const
Assign point indices for each edge label.
float getDepthDisconThreshold() const
Get the tolerance in meters for the relative difference in depth values between neighboring points.
void extractEdges(pcl::PointCloud< PointLT > &labels) const
Perform the 3D edge detection (edges from depth discontinuities) and assign point indices for each ed...
void setEdgeType(int edge_types)
Set the detecting edge types.
void setMaxSearchNeighbors(const int max_dist)
Set the max search distance for deciding occluding and occluded edges.
void compute(pcl::PointCloud< PointLT > &labels, std::vector< pcl::PointIndices > &label_indices) const
Perform the 3D edge detection (edges from depth discontinuities)
void setDepthDisconThreshold(const float th)
Set the tolerance in meters for the relative difference in depth values between neighboring points.
shared_ptr< const OrganizedEdgeBase< PointT, PointLT > > ConstPtr
shared_ptr< OrganizedEdgeBase< PointT, PointLT > > Ptr
int max_search_neighbors_
The max search distance for deciding occluding and occluded edges.
~OrganizedEdgeFromNormals()
Destructor for OrganizedEdgeFromNormals.
PointCloudNConstPtr getInputNormals() const
Get the input normals.
void compute(pcl::PointCloud< PointLT > &labels, std::vector< pcl::PointIndices > &label_indices) const
Perform the 3D edge detection (edges from depth discontinuities and high curvature regions) and assig...
PointCloudNConstPtr normals_
A pointer to the input normals.
void setHCCannyLowThreshold(const float th)
Set the low threshold value for high curvature Canny edge detection.
float th_hc_canny_high_
The high threshold value for high curvature Canny edge detection (default: 1.1)
void setHCCannyHighThreshold(const float th)
Set the high threshold value for high curvature Canny edge detection.
OrganizedEdgeFromNormals()
Constructor for OrganizedEdgeFromNormals.
float getHCCannyHighThreshold() const
Get the high threshold value for high curvature Canny edge detection.
void extractEdges(pcl::PointCloud< PointLT > &labels) const
Perform the 3D edge detection (edges from depth discontinuities and high curvature regions)
void setInputNormals(const PointCloudNConstPtr &normals)
Provide a pointer to the input normals.
float th_hc_canny_low_
The low threshold value for high curvature Canny edge detection (default: 0.4)
float getHCCannyLowThreshold() const
Get the low threshold value for high curvature Canny edge detection.
float getRGBCannyLowThreshold() const
Get the low threshold value for RGB Canny edge detection.
void extractEdges(pcl::PointCloud< PointLT > &labels) const
Perform the 3D edge detection (edges from depth discontinuities and RGB Canny edge)
float getRGBCannyHighThreshold() const
Get the high threshold value for RGB Canny edge detection.
~OrganizedEdgeFromRGB()
Destructor for OrganizedEdgeFromRGB.
OrganizedEdgeFromRGB()
Constructor for OrganizedEdgeFromRGB.
float th_rgb_canny_high_
The high threshold value for RGB Canny edge detection (default: 100.0)
void setRGBCannyLowThreshold(const float th)
Set the low threshold value for RGB Canny edge detection.
void setRGBCannyHighThreshold(const float th)
Set the high threshold value for RGB Canny edge detection.
float th_rgb_canny_low_
The low threshold value for RGB Canny edge detection (default: 40.0)
void compute(pcl::PointCloud< PointLT > &labels, std::vector< pcl::PointIndices > &label_indices) const
Perform the 3D edge detection (edges from depth discontinuities and RGB Canny edge) and assign point ...
void compute(pcl::PointCloud< PointLT > &labels, std::vector< pcl::PointIndices > &label_indices) const
Perform the 3D edge detection (edges from depth discontinuities, RGB Canny edge, and high curvature r...
~OrganizedEdgeFromRGBNormals()
Destructor for OrganizedEdgeFromRGBNormals.
OrganizedEdgeFromRGBNormals()
Constructor for OrganizedEdgeFromRGBNormals.
PCL base class.
Definition pcl_base.h:70
PointCloudConstPtr input_
The input point cloud dataset.
Definition pcl_base.h:147
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition pcl_base.h:150
bool initCompute()
This method should get called before starting the actual computation.
Definition pcl_base.hpp:138
bool deinitCompute()
This method should get called after finishing the actual computation.
Definition pcl_base.hpp:174
shared_ptr< const PointCloud< PointT > > ConstPtr
shared_ptr< PointCloud< PointT > > Ptr
A point structure representing Euclidean xyz coordinates, and the RGB color.