Point Cloud Library (PCL)
1.7.0
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Point Cloud Library (PCL) - www.pointclouds.org 00005 * Copyright (c) 2010-2012, Willow Garage, Inc. 00006 * 00007 * All rights reserved. 00008 * 00009 * Redistribution and use in source and binary forms, with or without 00010 * modification, are permitted provided that the following conditions 00011 * are met: 00012 * 00013 * * Redistributions of source code must retain the above copyright 00014 * notice, this list of conditions and the following disclaimer. 00015 * * Redistributions in binary form must reproduce the above 00016 * copyright notice, this list of conditions and the following 00017 * disclaimer in the documentation and/or other materials provided 00018 * with the distribution. 00019 * * Neither the name of the copyright holder(s) nor the names of its 00020 * contributors may be used to endorse or promote products derived 00021 * from this software without specific prior written permission. 00022 * 00023 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00024 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00025 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00026 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00027 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00028 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00029 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00030 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00031 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00032 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00033 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00034 * POSSIBILITY OF SUCH DAMAGE. 00035 * 00036 * $Id$ 00037 * 00038 */ 00039 00040 #ifndef PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_ 00041 #define PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_ 00042 00043 #include <pcl/filters/radius_outlier_removal.h> 00044 #include <pcl/common/io.h> 00045 00046 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00047 template <typename PointT> void 00048 pcl::RadiusOutlierRemoval<PointT>::applyFilter (PointCloud &output) 00049 { 00050 std::vector<int> indices; 00051 if (keep_organized_) 00052 { 00053 bool temp = extract_removed_indices_; 00054 extract_removed_indices_ = true; 00055 applyFilterIndices (indices); 00056 extract_removed_indices_ = temp; 00057 00058 output = *input_; 00059 for (int rii = 0; rii < static_cast<int> (removed_indices_->size ()); ++rii) // rii = removed indices iterator 00060 output.points[(*removed_indices_)[rii]].x = output.points[(*removed_indices_)[rii]].y = output.points[(*removed_indices_)[rii]].z = user_filter_value_; 00061 if (!pcl_isfinite (user_filter_value_)) 00062 output.is_dense = false; 00063 } 00064 else 00065 { 00066 applyFilterIndices (indices); 00067 copyPointCloud (*input_, indices, output); 00068 } 00069 } 00070 00071 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00072 template <typename PointT> void 00073 pcl::RadiusOutlierRemoval<PointT>::applyFilterIndices (std::vector<int> &indices) 00074 { 00075 if (search_radius_ == 0.0) 00076 { 00077 PCL_ERROR ("[pcl::%s::applyFilter] No radius defined!\n", getClassName ().c_str ()); 00078 indices.clear (); 00079 removed_indices_->clear (); 00080 return; 00081 } 00082 00083 // Initialize the search class 00084 if (!searcher_) 00085 { 00086 if (input_->isOrganized ()) 00087 searcher_.reset (new pcl::search::OrganizedNeighbor<PointT> ()); 00088 else 00089 searcher_.reset (new pcl::search::KdTree<PointT> (false)); 00090 } 00091 searcher_->setInputCloud (input_); 00092 00093 // The arrays to be used 00094 std::vector<int> nn_indices (indices_->size ()); 00095 std::vector<float> nn_dists (indices_->size ()); 00096 indices.resize (indices_->size ()); 00097 removed_indices_->resize (indices_->size ()); 00098 int oii = 0, rii = 0; // oii = output indices iterator, rii = removed indices iterator 00099 00100 for (std::vector<int>::const_iterator it = indices_->begin (); it != indices_->end (); ++it) 00101 { 00102 // Perform the radius search 00103 // Note: k includes the query point, so is always at least 1 00104 int k = searcher_->radiusSearch (*it, search_radius_, nn_indices, nn_dists); 00105 00106 // Points having too few neighbors are outliers and are passed to removed indices 00107 // Unless negative was set, then it's the opposite condition 00108 if ((!negative_ && k <= min_pts_radius_) || (negative_ && k > min_pts_radius_)) 00109 { 00110 if (extract_removed_indices_) 00111 (*removed_indices_)[rii++] = *it; 00112 continue; 00113 } 00114 00115 // Otherwise it was a normal point for output (inlier) 00116 indices[oii++] = *it; 00117 } 00118 00119 // Resize the output arrays 00120 indices.resize (oii); 00121 removed_indices_->resize (rii); 00122 } 00123 00124 #define PCL_INSTANTIATE_RadiusOutlierRemoval(T) template class PCL_EXPORTS pcl::RadiusOutlierRemoval<T>; 00125 00126 #endif // PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_ 00127