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#include <pcl/2d/edge.h>

Public Types
enum	OUTPUT_TYPE { OUTPUT_Y, OUTPUT_X, OUTPUT_X_Y, OUTPUT_MAGNITUDE, OUTPUT_DIRECTION, OUTPUT_MAGNITUDE_DIRECTION, OUTPUT_ALL }

enum	DETECTOR_KERNEL_TYPE { CANNY, SOBEL, PREWITT, ROBERTS, LOG, DERIVATIVE_CENTRAL, DERIVATIVE_FORWARD, DERIVATIVE_BACKWARD }

using	Ptr = shared_ptr< Edge< PointInT, PointOutT > >

using	ConstPtr = shared_ptr< const Edge< PointInT, PointOutT > >

Public Member Functions
	Edge ()

void	setOutputType (OUTPUT_TYPE output_type)
	Set the output type. More...

void	setHysteresisThresholdLow (float threshold)

void	setHysteresisThresholdHigh (float threshold)

void	sobelMagnitudeDirection (const pcl::PointCloud< PointInT > &input_x, const pcl::PointCloud< PointInT > &input_y, pcl::PointCloud< PointOutT > &output)

void	canny (const pcl::PointCloud< PointInT > &input_x, const pcl::PointCloud< PointInT > &input_y, pcl::PointCloud< PointOutT > &output)
	Perform Canny edge detection with two separated input images for horizontal and vertical derivatives. More...

void	detectEdge (pcl::PointCloud< PointOutT > &output)
	This is a convenience function which performs edge detection based on the variable detector_kernel_type_. More...

void	detectEdgeCanny (pcl::PointCloud< PointOutT > &output)
	All edges of magnitude above t_high are always classified as edges. More...

void	detectEdgeSobel (pcl::PointCloud< PointOutT > &output)
	Uses the Sobel kernel for edge detection. More...

void	detectEdgePrewitt (pcl::PointCloud< PointOutT > &output)
	Uses the Prewitt kernel for edge detection. More...

void	detectEdgeRoberts (pcl::PointCloud< PointOutT > &output)
	Uses the Roberts kernel for edge detection. More...

void	detectEdgeLoG (const float kernel_sigma, const float kernel_size, pcl::PointCloud< PointOutT > &output)
	Uses the LoG kernel for edge detection. More...

void	computeDerivativeXCentral (pcl::PointCloud< PointOutT > &output)
	Computes the image derivatives in X direction using the kernel kernel::derivativeYCentralKernel. More...

void	computeDerivativeYCentral (pcl::PointCloud< PointOutT > &output)
	Computes the image derivatives in Y direction using the kernel kernel::derivativeYCentralKernel. More...

void	computeDerivativeXForward (pcl::PointCloud< PointOutT > &output)
	Computes the image derivatives in X direction using the kernel kernel::derivativeYForwardKernel. More...

void	computeDerivativeYForward (pcl::PointCloud< PointOutT > &output)
	Computes the image derivatives in Y direction using the kernel kernel::derivativeYForwardKernel. More...

void	computeDerivativeXBackward (pcl::PointCloud< PointOutT > &output)
	Computes the image derivatives in X direction using the kernel kernel::derivativeXBackwardKernel. More...

void	computeDerivativeYBackward (pcl::PointCloud< PointOutT > &output)
	Computes the image derivatives in Y direction using the kernel kernel::derivativeYBackwardKernel. More...

void	applyFilter (pcl::PointCloud< PointOutT > &)
	Override function to implement the pcl::Filter interface. More...

void	setInputCloud (PointCloudInPtr input)
	Set the input point cloud pointer. More...

Detailed Description

template<typename PointInT, typename PointOutT>
class pcl::Edge< PointInT, PointOutT >

Definition at line 49 of file edge.h.

Member Typedef Documentation

ConstPtr

template<typename PointInT , typename PointOutT >

using pcl::Edge< PointInT, PointOutT >::ConstPtr = shared_ptr<const Edge<PointInT, PointOutT> >

Definition at line 93 of file edge.h.

Ptr

template<typename PointInT , typename PointOutT >

using pcl::Edge< PointInT, PointOutT >::Ptr = shared_ptr<Edge<PointInT, PointOutT> >

Definition at line 92 of file edge.h.

Member Enumeration Documentation

DETECTOR_KERNEL_TYPE

template<typename PointInT , typename PointOutT >

enum pcl::Edge::DETECTOR_KERNEL_TYPE

Enumerator
CANNY
SOBEL
PREWITT
ROBERTS
LOG
DERIVATIVE_CENTRAL
DERIVATIVE_FORWARD
DERIVATIVE_BACKWARD

Definition at line 105 of file edge.h.

OUTPUT_TYPE

template<typename PointInT , typename PointOutT >

enum pcl::Edge::OUTPUT_TYPE

Enumerator
OUTPUT_Y
OUTPUT_X
OUTPUT_X_Y
OUTPUT_MAGNITUDE
OUTPUT_DIRECTION
OUTPUT_MAGNITUDE_DIRECTION
OUTPUT_ALL

Definition at line 95 of file edge.h.

Constructor & Destructor Documentation

Edge()

template<typename PointInT , typename PointOutT >

pcl::Edge< PointInT, PointOutT >::Edge ( )

inline

Definition at line 128 of file edge.h.

Member Function Documentation

applyFilter()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::applyFilter ( pcl::PointCloud< PointOutT > & )

inline

Override function to implement the pcl::Filter interface.

Definition at line 297 of file edge.h.

canny()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::canny	(	const pcl::PointCloud< PointInT > &	input_x,
		const pcl::PointCloud< PointInT > &	input_y,
		pcl::PointCloud< PointOutT > &	output
	)

Perform Canny edge detection with two separated input images for horizontal and vertical derivatives.

All edges of magnitude above t_high are always classified as edges. All edges below t_low are discarded. Edge values between t_low and t_high are classified as edges only if they are connected to edges having magnitude > t_high and are located in a direction perpendicular to that strong edge.

Parameters

[in]	input_x	Input point cloud passed by reference for the first derivative in the horizontal direction
[in]	input_y	Input point cloud passed by reference for the first derivative in the vertical direction
[out]	output	Output point cloud passed by reference

Definition at line 376 of file edge.hpp.

Referenced by pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges().

computeDerivativeXBackward()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::computeDerivativeXBackward ( pcl::PointCloud< PointOutT > & output )

Computes the image derivatives in X direction using the kernel kernel::derivativeXBackwardKernel.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

output Output point cloud passed by reference

computeDerivativeXCentral()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::computeDerivativeXCentral ( pcl::PointCloud< PointOutT > & output )

Computes the image derivatives in X direction using the kernel kernel::derivativeYCentralKernel.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

computeDerivativeXForward()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::computeDerivativeXForward ( pcl::PointCloud< PointOutT > & output )

Computes the image derivatives in X direction using the kernel kernel::derivativeYForwardKernel.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

computeDerivativeYBackward()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::computeDerivativeYBackward ( pcl::PointCloud< PointOutT > & output )

Computes the image derivatives in Y direction using the kernel kernel::derivativeYBackwardKernel.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

computeDerivativeYCentral()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::computeDerivativeYCentral ( pcl::PointCloud< PointOutT > & output )

Computes the image derivatives in Y direction using the kernel kernel::derivativeYCentralKernel.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

computeDerivativeYForward()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::computeDerivativeYForward ( pcl::PointCloud< PointOutT > & output )

Computes the image derivatives in Y direction using the kernel kernel::derivativeYForwardKernel.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

detectEdge()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::detectEdge ( pcl::PointCloud< PointOutT > & output )

This is a convenience function which performs edge detection based on the variable detector_kernel_type_.

Parameters

[out] output

detectEdgeCanny()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::detectEdgeCanny ( pcl::PointCloud< PointOutT > & output )

All edges of magnitude above t_high are always classified as edges.

All edges below t_low are discarded. Edge values between t_low and t_high are classified as edges only if they are connected to edges having magnitude > t_high and are located in a direction perpendicular to that strong edge.

Parameters

[out] output Output point cloud passed by reference

Definition at line 312 of file edge.hpp.

Referenced by pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges().

detectEdgeLoG()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::detectEdgeLoG	(	const float	kernel_sigma,
		const float	kernel_size,
		pcl::PointCloud< PointOutT > &	output
	)

Uses the LoG kernel for edge detection.

Zero crossings of the Laplacian operator applied on an image indicate edges. Gaussian kernel is used to smoothen the image prior to the Laplacian. This is because Laplacian uses the second order derivative of the image and hence, is very sensitive to noise. The implementation is not two-step but rather applies the LoG kernel directly.

Parameters

[in]	kernel_sigma	variance of the LoG kernel used.
[in]	kernel_size	a LoG kernel of dimensions kernel_size x kernel_size is used.
[out]	output	Output point cloud passed by reference.

Definition at line 450 of file edge.hpp.

detectEdgePrewitt()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt ( pcl::PointCloud< PointOutT > & output )

Uses the Prewitt kernel for edge detection.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

Definition at line 126 of file edge.hpp.

detectEdgeRoberts()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::detectEdgeRoberts ( pcl::PointCloud< PointOutT > & output )

Uses the Roberts kernel for edge detection.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

Definition at line 164 of file edge.hpp.

detectEdgeSobel()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::detectEdgeSobel ( pcl::PointCloud< PointOutT > & output )

Uses the Sobel kernel for edge detection.

This function does NOT include a smoothing step. The image should be smoothed before using this function to reduce noise.

Parameters

[out] output Output point cloud passed by reference

Definition at line 48 of file edge.hpp.

setHysteresisThresholdHigh()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::setHysteresisThresholdHigh ( float threshold )

inline

Definition at line 155 of file edge.h.

Referenced by pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), and pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges().

setHysteresisThresholdLow()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::setHysteresisThresholdLow ( float threshold )

inline

Definition at line 149 of file edge.h.

Referenced by pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), and pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges().

setInputCloud()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::setInputCloud ( PointCloudInPtr input )

inline

Set the input point cloud pointer.

Parameters

[in] input pointer to input point cloud

Definition at line 304 of file edge.h.

Referenced by pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges().

setOutputType()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::setOutputType ( OUTPUT_TYPE output_type )

inline

Set the output type.

Parameters

[in] output_type the output type

Definition at line 143 of file edge.h.

sobelMagnitudeDirection()

template<typename PointInT , typename PointOutT >

void pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection	(	const pcl::PointCloud< PointInT > &	input_x,
		const pcl::PointCloud< PointInT > &	input_y,
		pcl::PointCloud< PointOutT > &	output
	)

Parameters

[in]	input_x
[in]	input_y
[out]	output

Definition at line 85 of file edge.hpp.

The documentation for this class was generated from the following files:

pcl/2d/edge.h
pcl/2d/impl/edge.hpp

© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_edge.html

Public Types

Public Member Functions

Detailed Description

template<typename PointInT, typename PointOutT> class pcl::Edge< PointInT, PointOutT >

Member Typedef Documentation

ConstPtr

Ptr

Member Enumeration Documentation

DETECTOR_KERNEL_TYPE

OUTPUT_TYPE

Constructor & Destructor Documentation

Edge()

Member Function Documentation

applyFilter()

canny()

computeDerivativeXBackward()

computeDerivativeXCentral()

computeDerivativeXForward()

computeDerivativeYBackward()

computeDerivativeYCentral()

computeDerivativeYForward()

detectEdge()

detectEdgeCanny()

detectEdgeLoG()

detectEdgePrewitt()

detectEdgeRoberts()

detectEdgeSobel()

setHysteresisThresholdHigh()

setHysteresisThresholdLow()

setInputCloud()

setOutputType()

sobelMagnitudeDirection()

template<typename PointInT, typename PointOutT>
class pcl::Edge< PointInT, PointOutT >