Implements the well known Region Growing algorithm used for segmentation. Description can be found in the article "Segmentation of point clouds using smoothness constraint" by T. Rabbania, F. A. van den Heuvelb, G. Vosselmanc. In addition to residual test, the possibility to test curvature is added. More...

#include <region_growing.h>

Inheritance diagram for pcl::RegionGrowing< PointT, NormalT >:

[legend]

List of all members.

Public Types
typedef pcl::search::Search < PointT >	KdTree
typedef KdTree::Ptr	KdTreePtr
typedef pcl::PointCloud< NormalT >	Normal
typedef Normal::Ptr	NormalPtr
typedef pcl::PointCloud< PointT >	PointCloud
Public Member Functions
virtual void	extract (std::vector< pcl::PointIndices > &clusters)
	This method launches the segmentation algorithm and returns the clusters that were obtained during the segmentation.
pcl::PointCloud < pcl::PointXYZRGB >::Ptr	getColoredCloud ()
	If the cloud was successfully segmented, then function returns colored cloud. Otherwise it returns an empty pointer. Points that belong to the same segment have the same color. But this function doesn't guarantee that different segments will have different color(it all depends on RNG). Points that were not listed in the indices array will have red color.
pcl::PointCloud < pcl::PointXYZRGBA >::Ptr	getColoredCloudRGBA ()
	If the cloud was successfully segmented, then function returns colored cloud. Otherwise it returns an empty pointer. Points that belong to the same segment have the same color. But this function doesn't guarantee that different segments will have different color(it all depends on RNG). Points that were not listed in the indices array will have red color.
bool	getCurvatureTestFlag () const
	Returns the flag that signalize if the curvature test is turned on/off.
float	getCurvatureThreshold () const
	Returns curvature threshold.
NormalPtr	getInputNormals () const
	Returns normals.
int	getMaxClusterSize ()
	Get the maximum number of points that a cluster needs to contain in order to be considered valid.
int	getMinClusterSize ()
	Get the minimum number of points that a cluster needs to contain in order to be considered valid.
unsigned int	getNumberOfNeighbours () const
	Returns the number of nearest neighbours used for KNN.
bool	getResidualTestFlag () const
	Returns the flag that signalize if the residual test is turned on/off.
float	getResidualThreshold () const
	Returns residual threshold.
KdTreePtr	getSearchMethod () const
	Returns the pointer to the search method that is used for KNN.
virtual void	getSegmentFromPoint (int index, pcl::PointIndices &cluster)
	For a given point this function builds a segment to which it belongs and returns this segment.
bool	getSmoothModeFlag () const
	Returns the flag value. This flag signalizes which mode of algorithm will be used. If it is set to true than it will work as said in the article. This means that it will be testing the angle between normal of the current point and it's neighbours normal. Otherwise, it will be testing the angle between normal of the current point and normal of the initial point that was chosen for growing new segment.
float	getSmoothnessThreshold () const
	Returns smoothness threshold.
	RegionGrowing ()
	Constructor that sets default values for member variables.
virtual void	setCurvatureTestFlag (bool value)
	Allows to turn on/off the curvature test. Note that at least one test (residual or curvature) must be turned on. If you are turning curvature test off then residual test will be turned on automatically.
void	setCurvatureThreshold (float curvature)
	Allows to set curvature threshold used for testing the points.
void	setInputNormals (const NormalPtr &norm)
	This method sets the normals. They are needed for the algorithm, so if no normals will be set, the algorithm would not be able to segment the points.
void	setMaxClusterSize (int max_cluster_size)
	Set the maximum number of points that a cluster needs to contain in order to be considered valid.
void	setMinClusterSize (int min_cluster_size)
	Set the minimum number of points that a cluster needs to contain in order to be considered valid.
void	setNumberOfNeighbours (unsigned int neighbour_number)
	Allows to set the number of neighbours. For more information check the article.
virtual void	setResidualTestFlag (bool value)
	Allows to turn on/off the residual test. Note that at least one test (residual or curvature) must be turned on. If you are turning residual test off then curvature test will be turned on automatically.
void	setResidualThreshold (float residual)
	Allows to set residual threshold used for testing the points.
void	setSearchMethod (const KdTreePtr &tree)
	Allows to set search method that will be used for finding KNN.
void	setSmoothModeFlag (bool value)
	This function allows to turn on/off the smoothness constraint.
void	setSmoothnessThreshold (float theta)
	Allows to set smoothness threshold used for testing the points.
virtual	~RegionGrowing ()
	This destructor destroys the cloud, normals and search method used for finding KNN. In other words it frees memory.
Protected Member Functions
void	applySmoothRegionGrowingAlgorithm ()
	This function implements the algorithm described in the article "Segmentation of point clouds using smoothness constraint" by T. Rabbania, F. A. van den Heuvelb, G. Vosselmanc.
void	assembleRegions ()
	This function simply assembles the regions from list of point labels.
virtual void	findPointNeighbours ()
	This method finds KNN for each point and saves them to the array because the algorithm needs to find KNN a few times.
int	growRegion (int initial_seed, int segment_number)
	This method grows a segment for the given seed point. And returns the number of its points.
virtual bool	prepareForSegmentation ()
	This method simply checks if it is possible to execute the segmentation algorithm with the current settings. If it is possible then it returns true.
virtual bool	validatePoint (int initial_seed, int point, int nghbr, bool &is_a_seed) const
	This function is checking if the point with index 'nghbr' belongs to the segment. If so, then it returns true. It also checks if this point can serve as the seed.
Protected Attributes
std::vector< pcl::PointIndices >	clusters_
	After the segmentation it will contain the segments.
bool	curvature_flag_
	If set to true then curvature test will be done during segmentation.
float	curvature_threshold_
	Thershold used in curvature test.
int	max_pts_per_cluster_
	Stores the maximum number of points that a cluster needs to contain in order to be considered valid.
int	min_pts_per_cluster_
	Stores the minimum number of points that a cluster needs to contain in order to be considered valid.
unsigned int	neighbour_number_
	Number of neighbours to find.
bool	normal_flag_
	If set to true then normal/smoothness test will be done during segmentation. It is always set to true for the usual region growing algorithm. It is used for turning on/off the test for smoothness in the child class RegionGrowingRGB.
NormalPtr	normals_
	Contains normals of the points that will be segmented.
std::vector< int >	num_pts_in_segment_
	Tells how much points each segment contains. Used for reserving memory.
int	number_of_segments_
	Stores the number of segments.
std::vector< int >	point_labels_
	Point labels that tells to which segment each point belongs.
std::vector< std::vector< int > >	point_neighbours_
	Contains neighbours of each point.
bool	residual_flag_
	If set to true then residual test will be done during segmentation.
float	residual_threshold_
	Thershold used in residual test.
KdTreePtr	search_
	Serch method that will be used for KNN.
bool	smooth_mode_flag_
	Flag that signalizes if the smoothness constraint will be used.
float	theta_threshold_
	Thershold used for testing the smoothness between points.

Detailed Description

template<typename PointT, typename NormalT>
class pcl::RegionGrowing< PointT, NormalT >

Implements the well known Region Growing algorithm used for segmentation. Description can be found in the article "Segmentation of point clouds using smoothness constraint" by T. Rabbania, F. A. van den Heuvelb, G. Vosselmanc. In addition to residual test, the possibility to test curvature is added.

Definition at line 61 of file region_growing.h.

Member Typedef Documentation

template<typename PointT, typename NormalT>

typedef pcl::search::Search<PointT> pcl::RegionGrowing< PointT, NormalT >::KdTree

Definition at line 65 of file region_growing.h.

template<typename PointT, typename NormalT>

typedef KdTree::Ptr pcl::RegionGrowing< PointT, NormalT >::KdTreePtr

Definition at line 66 of file region_growing.h.

template<typename PointT, typename NormalT>

typedef pcl::PointCloud<NormalT> pcl::RegionGrowing< PointT, NormalT >::Normal

Definition at line 67 of file region_growing.h.

template<typename PointT, typename NormalT>

typedef Normal::Ptr pcl::RegionGrowing< PointT, NormalT >::NormalPtr

Definition at line 68 of file region_growing.h.

template<typename PointT, typename NormalT>

typedef pcl::PointCloud<PointT> pcl::RegionGrowing< PointT, NormalT >::PointCloud

Reimplemented from pcl::PCLBase< PointT >.

Definition at line 69 of file region_growing.h.

Constructor & Destructor Documentation

template<typename PointT , typename NormalT >

pcl::RegionGrowing< PointT, NormalT >::RegionGrowing ( )

Constructor that sets default values for member variables.

Definition at line 57 of file region_growing.hpp.

template<typename PointT , typename NormalT >

pcl::RegionGrowing< PointT, NormalT >::~RegionGrowing ( ) [virtual]

This destructor destroys the cloud, normals and search method used for finding KNN. In other words it frees memory.

Definition at line 80 of file region_growing.hpp.

Member Function Documentation

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::applySmoothRegionGrowingAlgorithm ( ) [protected]

This function implements the algorithm described in the article "Segmentation of point clouds using smoothness constraint" by T. Rabbania, F. A. van den Heuvelb, G. Vosselmanc.

Definition at line 372 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::assembleRegions ( ) [protected]

This function simply assembles the regions from list of point labels.

Parameters:

[out] clusters clusters that were obtained during the segmentation process. Each cluster is an array of point indices.

Definition at line 532 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::extract ( std::vector< pcl::PointIndices > & clusters ) [virtual]

This method launches the segmentation algorithm and returns the clusters that were obtained during the segmentation.

Parameters:

[out] clusters clusters that were obtained. Each cluster is an array of point indices.

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 261 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::findPointNeighbours ( ) [protected, virtual]

This method finds KNN for each point and saves them to the array because the algorithm needs to find KNN a few times.

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 353 of file region_growing.hpp.

template<typename PointT , typename NormalT >

pcl::PointCloud< pcl::PointXYZRGB >::Ptr pcl::RegionGrowing< PointT, NormalT >::getColoredCloud ( )

If the cloud was successfully segmented, then function returns colored cloud. Otherwise it returns an empty pointer. Points that belong to the same segment have the same color. But this function doesn't guarantee that different segments will have different color(it all depends on RNG). Points that were not listed in the indices array will have red color.

Definition at line 634 of file region_growing.hpp.

template<typename PointT , typename NormalT >

pcl::PointCloud< pcl::PointXYZRGBA >::Ptr pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA ( )

If the cloud was successfully segmented, then function returns colored cloud. Otherwise it returns an empty pointer. Points that belong to the same segment have the same color. But this function doesn't guarantee that different segments will have different color(it all depends on RNG). Points that were not listed in the indices array will have red color.

Definition at line 688 of file region_growing.hpp.

template<typename PointT , typename NormalT >

bool pcl::RegionGrowing< PointT, NormalT >::getCurvatureTestFlag ( ) const

Returns the flag that signalize if the curvature test is turned on/off.

Definition at line 137 of file region_growing.hpp.

template<typename PointT , typename NormalT >

float pcl::RegionGrowing< PointT, NormalT >::getCurvatureThreshold ( ) const

Returns curvature threshold.

Definition at line 199 of file region_growing.hpp.

template<typename PointT , typename NormalT >

pcl::RegionGrowing< PointT, NormalT >::NormalPtr pcl::RegionGrowing< PointT, NormalT >::getInputNormals ( ) const

Returns normals.

Definition at line 244 of file region_growing.hpp.

template<typename PointT , typename NormalT >

int pcl::RegionGrowing< PointT, NormalT >::getMaxClusterSize ( )

Get the maximum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 109 of file region_growing.hpp.

template<typename PointT , typename NormalT >

int pcl::RegionGrowing< PointT, NormalT >::getMinClusterSize ( )

Get the minimum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 95 of file region_growing.hpp.

template<typename PointT , typename NormalT >

unsigned int pcl::RegionGrowing< PointT, NormalT >::getNumberOfNeighbours ( ) const

Returns the number of nearest neighbours used for KNN.

Definition at line 213 of file region_growing.hpp.

template<typename PointT , typename NormalT >

bool pcl::RegionGrowing< PointT, NormalT >::getResidualTestFlag ( ) const

Returns the flag that signalize if the residual test is turned on/off.

Definition at line 154 of file region_growing.hpp.

template<typename PointT , typename NormalT >

float pcl::RegionGrowing< PointT, NormalT >::getResidualThreshold ( ) const

Returns residual threshold.

Definition at line 185 of file region_growing.hpp.

template<typename PointT , typename NormalT >

pcl::RegionGrowing< PointT, NormalT >::KdTreePtr pcl::RegionGrowing< PointT, NormalT >::getSearchMethod ( ) const

Returns the pointer to the search method that is used for KNN.

Definition at line 227 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::getSegmentFromPoint	(	int	index,
		pcl::PointIndices &	cluster
	)		`[virtual]`

For a given point this function builds a segment to which it belongs and returns this segment.

Parameters:

[in]	index	index of the initial point which will be the seed for growing a segment.
[out]	cluster	cluster to which the point belongs.

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 564 of file region_growing.hpp.

template<typename PointT , typename NormalT >

bool pcl::RegionGrowing< PointT, NormalT >::getSmoothModeFlag ( ) const

Returns the flag value. This flag signalizes which mode of algorithm will be used. If it is set to true than it will work as said in the article. This means that it will be testing the angle between normal of the current point and it's neighbours normal. Otherwise, it will be testing the angle between normal of the current point and normal of the initial point that was chosen for growing new segment.

Definition at line 123 of file region_growing.hpp.

template<typename PointT , typename NormalT >

float pcl::RegionGrowing< PointT, NormalT >::getSmoothnessThreshold ( ) const

Returns smoothness threshold.

Definition at line 171 of file region_growing.hpp.

template<typename PointT , typename NormalT >

int pcl::RegionGrowing< PointT, NormalT >::growRegion	(	int	initial_seed,
		int	segment_number
	)		`[protected]`

This method grows a segment for the given seed point. And returns the number of its points.

Parameters:

[in]	initial_seed	index of the point that will serve as the seed point
[in]	segment_number	indicates which number this segment will have

Definition at line 428 of file region_growing.hpp.

template<typename PointT , typename NormalT >

bool pcl::RegionGrowing< PointT, NormalT >::prepareForSegmentation ( ) [protected, virtual]

This method simply checks if it is possible to execute the segmentation algorithm with the current settings. If it is possible then it returns true.

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 307 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setCurvatureTestFlag ( bool value ) [virtual]

Allows to turn on/off the curvature test. Note that at least one test (residual or curvature) must be turned on. If you are turning curvature test off then residual test will be turned on automatically.

Parameters:

[in] value new value for curvature test. If set to true then the test will be turned on

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 144 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setCurvatureThreshold ( float curvature )

Allows to set curvature threshold used for testing the points.

Parameters:

[in] curvature new threshold value for curvature testing

Definition at line 206 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setInputNormals ( const NormalPtr & norm )

This method sets the normals. They are needed for the algorithm, so if no normals will be set, the algorithm would not be able to segment the points.

Parameters:

[in] norm normals that will be used in the algorithm

Definition at line 251 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setMaxClusterSize ( int max_cluster_size )

Set the maximum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 116 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setMinClusterSize ( int min_cluster_size )

Set the minimum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 102 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setNumberOfNeighbours ( unsigned int neighbour_number )

Allows to set the number of neighbours. For more information check the article.

Parameters:

[in] neighbour_number number of neighbours to use

Definition at line 220 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setResidualTestFlag ( bool value ) [virtual]

Allows to turn on/off the residual test. Note that at least one test (residual or curvature) must be turned on. If you are turning residual test off then curvature test will be turned on automatically.

Parameters:

[in] value new value for residual test. If set to true then the test will be turned on

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 161 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setResidualThreshold ( float residual )

Allows to set residual threshold used for testing the points.

Parameters:

[in] residual new threshold value for residual testing

Definition at line 192 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setSearchMethod ( const KdTreePtr & tree )

Allows to set search method that will be used for finding KNN.

Parameters:

[in] search search method to use

Definition at line 234 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setSmoothModeFlag ( bool value )

This function allows to turn on/off the smoothness constraint.

Parameters:

[in] value new mode value, if set to true then the smooth version will be used.

Definition at line 130 of file region_growing.hpp.

template<typename PointT , typename NormalT >

void pcl::RegionGrowing< PointT, NormalT >::setSmoothnessThreshold ( float theta )

Allows to set smoothness threshold used for testing the points.

Parameters:

[in] theta new threshold value for the angle between normals

Definition at line 178 of file region_growing.hpp.

template<typename PointT , typename NormalT >

bool pcl::RegionGrowing< PointT, NormalT >::validatePoint	(	int	initial_seed,
		int	point,
		int	nghbr,
		bool &	is_a_seed
	)		const `[protected, virtual]`

This function is checking if the point with index 'nghbr' belongs to the segment. If so, then it returns true. It also checks if this point can serve as the seed.

Parameters:

[in]	initial_seed	index of the initial point that was passed to the growRegion() function
[in]	point	index of the current seed point
[in]	nghbr	index of the point that is neighbour of the current seed
[out]	is_a_seed	this value is set to true if the point with index 'nghbr' can serve as the seed

Reimplemented in pcl::RegionGrowingRGB< PointT, NormalT >.

Definition at line 478 of file region_growing.hpp.

Member Data Documentation

template<typename PointT, typename NormalT>

std::vector<pcl::PointIndices> pcl::RegionGrowing< PointT, NormalT >::clusters_ [protected]

After the segmentation it will contain the segments.

Definition at line 331 of file region_growing.h.

template<typename PointT, typename NormalT>

bool pcl::RegionGrowing< PointT, NormalT >::curvature_flag_ [protected]

If set to true then curvature test will be done during segmentation.

Definition at line 293 of file region_growing.h.

template<typename PointT, typename NormalT>

float pcl::RegionGrowing< PointT, NormalT >::curvature_threshold_ [protected]

Thershold used in curvature test.

Definition at line 305 of file region_growing.h.

template<typename PointT, typename NormalT>

int pcl::RegionGrowing< PointT, NormalT >::max_pts_per_cluster_ [protected]

Stores the maximum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 287 of file region_growing.h.

template<typename PointT, typename NormalT>

int pcl::RegionGrowing< PointT, NormalT >::min_pts_per_cluster_ [protected]

Stores the minimum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 284 of file region_growing.h.

template<typename PointT, typename NormalT>

unsigned int pcl::RegionGrowing< PointT, NormalT >::neighbour_number_ [protected]

Number of neighbours to find.

Definition at line 308 of file region_growing.h.

template<typename PointT, typename NormalT>

bool pcl::RegionGrowing< PointT, NormalT >::normal_flag_ [protected]

If set to true then normal/smoothness test will be done during segmentation. It is always set to true for the usual region growing algorithm. It is used for turning on/off the test for smoothness in the child class RegionGrowingRGB.

Definition at line 325 of file region_growing.h.

template<typename PointT, typename NormalT>

NormalPtr pcl::RegionGrowing< PointT, NormalT >::normals_ [protected]

Contains normals of the points that will be segmented.

Definition at line 314 of file region_growing.h.

template<typename PointT, typename NormalT>

std::vector<int> pcl::RegionGrowing< PointT, NormalT >::num_pts_in_segment_ [protected]

Tells how much points each segment contains. Used for reserving memory.

Definition at line 328 of file region_growing.h.

template<typename PointT, typename NormalT>

int pcl::RegionGrowing< PointT, NormalT >::number_of_segments_ [protected]

Stores the number of segments.