315 lines
11 KiB
C
315 lines
11 KiB
C
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2012-, Open Perception, Inc.
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of the copyright holder(s) nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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*/
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#pragma once
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#include <pcl/2d/convolution.h>
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#include <pcl/2d/kernel.h>
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#include <pcl/memory.h>
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#include <pcl/pcl_base.h>
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#include <pcl/pcl_macros.h>
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namespace pcl {
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template <typename PointInT, typename PointOutT>
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class Edge {
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private:
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using PointCloudIn = pcl::PointCloud<PointInT>;
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using PointCloudInPtr = typename PointCloudIn::Ptr;
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PointCloudInPtr input_;
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pcl::Convolution<PointInT> convolution_;
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kernel<PointInT> kernel_;
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/** \brief This function performs edge tracing for Canny Edge detector.
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*
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* \param[in] rowOffset row offset for direction in which the edge is to be traced
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* \param[in] colOffset column offset for direction in which the edge is to be traced
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* \param[in] row row location of the edge point
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* \param[in] col column location of the edge point
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* \param[out] maxima point cloud containing the edge information in the magnitude
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* channel
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*/
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inline void
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cannyTraceEdge(int rowOffset,
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int colOffset,
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int row,
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int col,
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pcl::PointCloud<pcl::PointXYZI>& maxima);
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/** \brief This function discretizes the edge directions in steps of 22.5 degrees.
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* \param thet point cloud containing the edge information in the direction channel
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*/
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void
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discretizeAngles(pcl::PointCloud<PointOutT>& thet);
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/** \brief This function suppresses the edges which don't form a local maximum
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* in the edge direction.
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* \param[in] edges point cloud containing all the edges
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* \param[out] maxima point cloud containing the non-max suppressed edges
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* \param[in] tLow
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*/
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void
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suppressNonMaxima(const pcl::PointCloud<PointXYZIEdge>& edges,
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pcl::PointCloud<pcl::PointXYZI>& maxima,
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float tLow);
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public:
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using Ptr = shared_ptr<Edge<PointInT, PointOutT>>;
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using ConstPtr = shared_ptr<const Edge<PointInT, PointOutT>>;
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enum OUTPUT_TYPE {
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OUTPUT_Y,
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OUTPUT_X,
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OUTPUT_X_Y,
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OUTPUT_MAGNITUDE,
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OUTPUT_DIRECTION,
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OUTPUT_MAGNITUDE_DIRECTION,
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OUTPUT_ALL
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};
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enum DETECTOR_KERNEL_TYPE {
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CANNY,
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SOBEL,
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PREWITT,
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ROBERTS,
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LOG,
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DERIVATIVE_CENTRAL,
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DERIVATIVE_FORWARD,
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DERIVATIVE_BACKWARD
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};
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private:
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OUTPUT_TYPE output_type_;
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DETECTOR_KERNEL_TYPE detector_kernel_type_;
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bool non_maximal_suppression_;
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bool hysteresis_thresholding_;
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float hysteresis_threshold_low_;
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float hysteresis_threshold_high_;
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float non_max_suppression_radius_x_;
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float non_max_suppression_radius_y_;
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public:
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Edge()
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: output_type_(OUTPUT_X)
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, detector_kernel_type_(SOBEL)
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, non_maximal_suppression_(false)
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, hysteresis_thresholding_(false)
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, hysteresis_threshold_low_(20)
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, hysteresis_threshold_high_(80)
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, non_max_suppression_radius_x_(3)
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, non_max_suppression_radius_y_(3)
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{}
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/** \brief Set the output type.
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* \param[in] output_type the output type
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*/
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void
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setOutputType(OUTPUT_TYPE output_type)
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{
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output_type_ = output_type;
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}
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void
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setHysteresisThresholdLow(float threshold)
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{
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hysteresis_threshold_low_ = threshold;
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}
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void
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setHysteresisThresholdHigh(float threshold)
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{
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hysteresis_threshold_high_ = threshold;
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}
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/**
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* \param[in] input_x
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* \param[in] input_y
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* \param[out] output
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*/
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void
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sobelMagnitudeDirection(const pcl::PointCloud<PointInT>& input_x,
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const pcl::PointCloud<PointInT>& input_y,
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pcl::PointCloud<PointOutT>& output);
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/** Perform Canny edge detection with two separated input images for horizontal and
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* vertical derivatives.
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*
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* All edges of magnitude above t_high are always classified as edges. All edges
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* below t_low are discarded. Edge values between t_low and t_high are classified
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* as edges only if they are connected to edges having magnitude > t_high and are
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* located in a direction perpendicular to that strong edge.
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*
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* \param[in] input_x Input point cloud passed by reference for the first derivative
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* in the horizontal direction
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* \param[in] input_y Input point cloud passed by reference for the first derivative
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* in the vertical direction
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* \param[out] output Output point cloud passed by reference
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*/
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void
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canny(const pcl::PointCloud<PointInT>& input_x,
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const pcl::PointCloud<PointInT>& input_y,
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pcl::PointCloud<PointOutT>& output);
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/** \brief This is a convenience function which performs edge detection based on
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* the variable detector_kernel_type_
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* \param[out] output
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*/
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void
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detectEdge(pcl::PointCloud<PointOutT>& output);
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/** \brief All edges of magnitude above t_high are always classified as edges.
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* All edges below t_low are discarded.
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* Edge values between t_low and t_high are classified as edges only if they are
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* connected to edges having magnitude > t_high and are located in a direction
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* perpendicular to that strong edge.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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detectEdgeCanny(pcl::PointCloud<PointOutT>& output);
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/** \brief Uses the Sobel kernel for edge detection.
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* This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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detectEdgeSobel(pcl::PointCloud<PointOutT>& output);
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/** \brief Uses the Prewitt kernel for edge detection.
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* This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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detectEdgePrewitt(pcl::PointCloud<PointOutT>& output);
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/** \brief Uses the Roberts kernel for edge detection.
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* This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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detectEdgeRoberts(pcl::PointCloud<PointOutT>& output);
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/** \brief Uses the LoG kernel for edge detection.
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* Zero crossings of the Laplacian operator applied on an image indicate edges.
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* Gaussian kernel is used to smoothen the image prior to the Laplacian.
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* This is because Laplacian uses the second order derivative of the image and hence,
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* is very sensitive to noise. The implementation is not two-step but rather applies
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* the LoG kernel directly.
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*
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* \param[in] kernel_sigma variance of the LoG kernel used.
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* \param[in] kernel_size a LoG kernel of dimensions kernel_size x kernel_size is
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* used.
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* \param[out] output Output point cloud passed by reference.
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*/
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void
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detectEdgeLoG(const float kernel_sigma,
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const float kernel_size,
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pcl::PointCloud<PointOutT>& output);
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/** \brief Computes the image derivatives in X direction using the kernel
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* kernel::derivativeYCentralKernel. This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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computeDerivativeXCentral(pcl::PointCloud<PointOutT>& output);
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/** \brief Computes the image derivatives in Y direction using the kernel
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* kernel::derivativeYCentralKernel. This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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computeDerivativeYCentral(pcl::PointCloud<PointOutT>& output);
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/** \brief Computes the image derivatives in X direction using the kernel
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* kernel::derivativeYForwardKernel. This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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computeDerivativeXForward(pcl::PointCloud<PointOutT>& output);
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/** \brief Computes the image derivatives in Y direction using the kernel
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* kernel::derivativeYForwardKernel. This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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computeDerivativeYForward(pcl::PointCloud<PointOutT>& output);
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/** \brief Computes the image derivatives in X direction using the kernel
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* kernel::derivativeXBackwardKernel. This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param output Output point cloud passed by reference
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*/
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void
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computeDerivativeXBackward(pcl::PointCloud<PointOutT>& output);
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/** \brief Computes the image derivatives in Y direction using the kernel
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* kernel::derivativeYBackwardKernel. This function does NOT include a smoothing step.
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* The image should be smoothed before using this function to reduce noise.
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* \param[out] output Output point cloud passed by reference
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*/
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void
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computeDerivativeYBackward(pcl::PointCloud<PointOutT>& output);
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/** \brief Override function to implement the pcl::Filter interface */
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void
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applyFilter(pcl::PointCloud<PointOutT>& /*output*/)
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{}
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/** \brief Set the input point cloud pointer
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* \param[in] input pointer to input point cloud
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*/
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void
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setInputCloud(PointCloudInPtr input)
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{
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input_ = input;
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}
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PCL_MAKE_ALIGNED_OPERATOR_NEW
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};
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} // namespace pcl
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#include <pcl/2d/impl/edge.hpp>
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