Program Listing for File edge.h¶
↰ Return to documentation for file (pcl\2d\include\pcl\2d\edge.h)
/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2012-, Open Perception, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
*/
#ifndef PCL_2D_EDGE_H
#define PCL_2D_EDGE_H
#include <pcl/pcl_base.h>
#include <pcl/2d/convolution.h>
#include <pcl/2d/kernel.h>
namespace pcl
{
template <typename PointInT, typename PointOutT>
class Edge
{
private:
typedef typename pcl::PointCloud<PointInT> PointCloudIn;
typedef typename PointCloudIn::Ptr PointCloudInPtr;
PointCloudInPtr input_;
pcl::Convolution<PointInT> convolution_;
kernel<PointInT> kernel_;
/** \brief This function performs edge tracing for Canny Edge detector.
*
* \param[in] rowOffset row offset for direction in which the edge is to be traced
* \param[in] colOffset column offset for direction in which the edge is to be traced
* \param[in] row row location of the edge point
* \param[in] col column location of the edge point
* \param[out] maxima point cloud containing the edge information in the magnitude channel
*/
inline void
cannyTraceEdge (int rowOffset, int colOffset, int row, int col,
pcl::PointCloud<pcl::PointXYZI> &maxima);
/** \brief This function discretizes the edge directions in steps of 22.5 degrees.
* \param thet point cloud containing the edge information in the direction channel
*/
void
discretizeAngles (pcl::PointCloud<PointOutT> &thet);
/** \brief This function suppresses the edges which don't form a local maximum
* in the edge direction.
* \param[in] edges point cloud containing all the edges
* \param[out] maxima point cloud containing the non-max suppressed edges
* \param[in] tLow
*/
void
suppressNonMaxima (const pcl::PointCloud<PointXYZIEdge> &edges,
pcl::PointCloud<pcl::PointXYZI> &maxima, float tLow);
public:
typedef boost::shared_ptr<Edge> Ptr;
typedef boost::shared_ptr<const Edge> ConstPtr;
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
};
private:
OUTPUT_TYPE output_type_;
DETECTOR_KERNEL_TYPE detector_kernel_type_;
bool non_maximal_suppression_;
bool hysteresis_thresholding_;
float hysteresis_threshold_low_;
float hysteresis_threshold_high_;
float non_max_suppression_radius_x_;
float non_max_suppression_radius_y_;
public:
Edge () :
output_type_ (OUTPUT_X),
detector_kernel_type_ (SOBEL),
non_maximal_suppression_ (false),
hysteresis_thresholding_ (false),
hysteresis_threshold_low_ (20),
hysteresis_threshold_high_ (80),
non_max_suppression_radius_x_ (3),
non_max_suppression_radius_y_ (3)
{
}
/** \brief Set the output type.
* \param[in] output_type the output type
*/
void
setOutputType (OUTPUT_TYPE output_type)
{
output_type_ = output_type;
}
void
setHysteresisThresholdLow (float threshold)
{
hysteresis_threshold_low_ = threshold;
}
void
setHysteresisThresholdHigh (float threshold)
{
hysteresis_threshold_high_ = threshold;
}
/**
* \param[in] input_x
* \param[in] input_y
* \param[out] output
*/
void
sobelMagnitudeDirection (const pcl::PointCloud<PointInT> &input_x,
const pcl::PointCloud<PointInT> &input_y,
pcl::PointCloud<PointOutT> &output);
/** \brief 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.
*
* \param[in] input_x Input point cloud passed by reference for the first derivative in the horizontal direction
* \param[in] input_y Input point cloud passed by reference for the first derivative in the vertical direction
* \param[out] output Output point cloud passed by reference
*/
void
canny (const pcl::PointCloud<PointInT> &input_x,
const pcl::PointCloud<PointInT> &input_y,
pcl::PointCloud<PointOutT> &output);
/** \brief This is a convenience function which performs edge detection based on
* the variable detector_kernel_type_
* \param[out] output
*/
void
detectEdge (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
detectEdgeCanny (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
detectEdgeSobel (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
detectEdgePrewitt (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
detectEdgeRoberts (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
*
* \param[in] kernel_sigma variance of the LoG kernel used.
* \param[in] kernel_size a LoG kernel of dimensions kernel_size x kernel_size is used.
* \param[out] output Output point cloud passed by reference.
*/
void
detectEdgeLoG (const float kernel_sigma, const float kernel_size,
pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
computeDerivativeXCentral (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
computeDerivativeYCentral (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
computeDerivativeXForward (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
computeDerivativeYForward (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param output Output point cloud passed by reference
*/
void
computeDerivativeXBackward (pcl::PointCloud<PointOutT> &output);
/** \brief 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.
* \param[out] output Output point cloud passed by reference
*/
void
computeDerivativeYBackward (pcl::PointCloud<PointOutT> &output);
/** \brief Override function to implement the pcl::Filter interface
*/
void
applyFilter (pcl::PointCloud<PointOutT>& /*output*/) {}
/** \brief Set the input point cloud pointer
* \param[in] input pointer to input point cloud
*/
void
setInputCloud (PointCloudInPtr input)
{
input_ = input;
}
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};
}
#include <pcl/2d/impl/edge.hpp>
#endif // PCL_2D_EDGE_H