/* * Software License Agreement (BSD License) * * Point Cloud Library (PCL) - www.pointclouds.org * Copyright (c) 2012, Yani Ioannou * 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. * */ #pragma once #include namespace pcl { /** \brief A Difference of Normals (DoN) scale filter implementation for point cloud data. * * For each point in the point cloud two normals estimated with a differing search radius (sigma_s, sigma_l) * are subtracted, the difference of these normals provides a scale-based feature which * can be further used to filter the point cloud, somewhat like the Difference of Guassians * in image processing, but instead on surfaces. Best results are had when the two search * radii are related as sigma_l=10*sigma_s, the octaves between the two search radii * can be though of as a filter bandwidth. For appropriate values and thresholds it * can be used for surface edge extraction. * * \attention The input normals given by setInputNormalsSmall and setInputNormalsLarge have * to match the input point cloud given by setInputCloud. This behavior is different than * feature estimation methods that extend FeatureFromNormals, which match the normals * with the search surface. * * \note For more information please see * Yani Ioannou. Automatic Urban Modelling using Mobile Urban LIDAR Data. * Thesis (Master, Computing), Queen's University, March, 2010. * * \author Yani Ioannou. * \ingroup features */ template class DifferenceOfNormalsEstimation : public Feature { using Feature::getClassName; using Feature::feature_name_; using PCLBase::input_; using PointCloudN = pcl::PointCloud; using PointCloudNPtr = typename PointCloudN::Ptr; using PointCloudNConstPtr = typename PointCloudN::ConstPtr; using PointCloudOut = typename Feature::PointCloudOut; public: using Ptr = shared_ptr >; using ConstPtr = shared_ptr >; /** * Creates a new Difference of Normals filter. */ DifferenceOfNormalsEstimation () { feature_name_ = "DifferenceOfNormalsEstimation"; } ~DifferenceOfNormalsEstimation () { // } /** * Set the normals calculated using a smaller search radius (scale) for the DoN operator. * @param normals the smaller radius (scale) of the DoN filter. */ inline void setNormalScaleSmall (const PointCloudNConstPtr &normals) { input_normals_small_ = normals; } /** * Set the normals calculated using a larger search radius (scale) for the DoN operator. * @param normals the larger radius (scale) of the DoN filter. */ inline void setNormalScaleLarge (const PointCloudNConstPtr &normals) { input_normals_large_ = normals; } /** * Computes the DoN vector for each point in the input point cloud and outputs the vector cloud to the given output. * @param output the cloud to output the DoN vector cloud to. */ void computeFeature (PointCloudOut &output) override; /** * Initialize for computation of features. * @return true if parameters (input normals, input) are sufficient to perform computation. */ bool initCompute () override; private: /** \brief Make the compute (&PointCloudOut); inaccessible from outside the class * \param[out] output the output point cloud */ void compute (PointCloudOut &) {} ///The smallest radius (scale) used in the DoN filter. PointCloudNConstPtr input_normals_small_; ///The largest radius (scale) used in the DoN filter. PointCloudNConstPtr input_normals_large_; }; } #ifdef PCL_NO_PRECOMPILE #include #endif