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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2012, Yani Ioannou <yani.ioannou@gmail.com>
* 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 <pcl/features/feature.h>
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
* <b>Yani Ioannou. Automatic Urban Modelling using Mobile Urban LIDAR Data.
* Thesis (Master, Computing), Queen's University, March, 2010.</b>
*
* \author Yani Ioannou.
* \ingroup features
*/
template <typename PointInT, typename PointNT, typename PointOutT>
class DifferenceOfNormalsEstimation : public Feature<PointInT, PointOutT>
{
using Feature<PointInT, PointOutT>::getClassName;
using Feature<PointInT, PointOutT>::feature_name_;
using PCLBase<PointInT>::input_;
using PointCloudN = pcl::PointCloud<PointNT>;
using PointCloudNPtr = typename PointCloudN::Ptr;
using PointCloudNConstPtr = typename PointCloudN::ConstPtr;
using PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut;
public:
using Ptr = shared_ptr<DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT> >;
using ConstPtr = shared_ptr<const DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT> >;
/**
* 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 <pcl/features/impl/don.hpp>
#endif