Point Cloud Library (PCL)
1.10.0
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40 #include <pcl/2d/convolution.h>
41 #include <pcl/2d/kernel.h>
42 #include <pcl/pcl_base.h>
47 template <
typename Po
intInT,
typename Po
intOutT>
53 PointCloudInPtr input_;
67 cannyTraceEdge(
int rowOffset,
118 bool non_maximal_suppression_;
119 bool hysteresis_thresholding_;
121 float hysteresis_threshold_low_;
122 float hysteresis_threshold_high_;
123 float non_max_suppression_radius_x_;
124 float non_max_suppression_radius_y_;
129 , detector_kernel_type_(
SOBEL)
130 , non_maximal_suppression_(false)
131 , hysteresis_thresholding_(false)
132 , hysteresis_threshold_low_(20)
133 , hysteresis_threshold_high_(80)
134 , non_max_suppression_radius_x_(3)
135 , non_max_suppression_radius_y_(3)
144 output_type_ = output_type;
150 hysteresis_threshold_low_ = threshold;
156 hysteresis_threshold_high_ = threshold;
243 const float kernel_size,
313 #include <pcl/2d/impl/edge.hpp>
Defines all the PCL and non-PCL macros used.
This file defines compatibility wrappers for low level I/O functions.
void sobelMagnitudeDirection(const pcl::PointCloud< PointInT > &input_x, const pcl::PointCloud< PointInT > &input_y, pcl::PointCloud< PointOutT > &output)
void applyFilter(pcl::PointCloud< PointOutT > &)
Override function to implement the pcl::Filter interface.
void setInputCloud(PointCloudInPtr input)
Set the input point cloud pointer.
void computeDerivativeYForward(pcl::PointCloud< PointOutT > &output)
Computes the image derivatives in Y direction using the kernel kernel::derivativeYForwardKernel.
void detectEdgeRoberts(pcl::PointCloud< PointOutT > &output)
Uses the Roberts kernel for edge detection.
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.
shared_ptr< const Edge< PointInT, PointOutT > > ConstPtr
void detectEdgePrewitt(pcl::PointCloud< PointOutT > &output)
Uses the Prewitt kernel for edge detection.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
void setHysteresisThresholdLow(float threshold)
void computeDerivativeXForward(pcl::PointCloud< PointOutT > &output)
Computes the image derivatives in X direction using the kernel kernel::derivativeYForwardKernel.
void detectEdge(pcl::PointCloud< PointOutT > &output)
This is a convenience function which performs edge detection based on the variable detector_kernel_ty...
void computeDerivativeYBackward(pcl::PointCloud< PointOutT > &output)
Computes the image derivatives in Y direction using the kernel kernel::derivativeYBackwardKernel.
shared_ptr< PointCloud< PointInT > > Ptr
void computeDerivativeXCentral(pcl::PointCloud< PointOutT > &output)
Computes the image derivatives in X direction using the kernel kernel::derivativeYCentralKernel.
void computeDerivativeYCentral(pcl::PointCloud< PointOutT > &output)
Computes the image derivatives in Y direction using the kernel kernel::derivativeYCentralKernel.
void setHysteresisThresholdHigh(float threshold)
void detectEdgeSobel(pcl::PointCloud< PointOutT > &output)
Uses the Sobel kernel for edge detection.
shared_ptr< Edge< PointInT, PointOutT > > Ptr
void detectEdgeCanny(pcl::PointCloud< PointOutT > &output)
All edges of magnitude above t_high are always classified as edges.
void setOutputType(OUTPUT_TYPE output_type)
Set the output type.
void computeDerivativeXBackward(pcl::PointCloud< PointOutT > &output)
Computes the image derivatives in X direction using the kernel kernel::derivativeXBackwardKernel.
void detectEdgeLoG(const float kernel_sigma, const float kernel_size, pcl::PointCloud< PointOutT > &output)
Uses the LoG kernel for edge detection.
boost::shared_ptr< T > shared_ptr
Alias for boost::shared_ptr.