Point Cloud Library (PCL)
1.12.1
Toggle main menu visibility
Loading...
Searching...
No Matches
pcl
features
don.h
1
/*
2
* Software License Agreement (BSD License)
3
*
4
* Point Cloud Library (PCL) - www.pointclouds.org
5
* Copyright (c) 2012, Yani Ioannou <yani.ioannou@gmail.com>
6
* Copyright (c) 2012-, Open Perception, Inc.
7
*
8
* All rights reserved.
9
*
10
* Redistribution and use in source and binary forms, with or without
11
* modification, are permitted provided that the following conditions
12
* are met:
13
*
14
* * Redistributions of source code must retain the above copyright
15
* notice, this list of conditions and the following disclaimer.
16
* * Redistributions in binary form must reproduce the above
17
* copyright notice, this list of conditions and the following
18
* disclaimer in the documentation and/or other materials provided
19
* with the distribution.
20
* * Neither the name of the copyright holder(s) nor the names of its
21
* contributors may be used to endorse or promote products derived
22
* from this software without specific prior written permission.
23
*
24
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
25
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
26
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
27
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
28
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
29
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
30
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
31
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
32
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
33
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
34
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
35
* POSSIBILITY OF SUCH DAMAGE.
36
*
37
*/
38
39
#pragma once
40
41
#include <pcl/features/feature.h>
42
43
namespace
pcl
44
{
45
/** \brief A Difference of Normals (DoN) scale filter implementation for point cloud data.
46
*
47
* For each point in the point cloud two normals estimated with a differing search radius (sigma_s, sigma_l)
48
* are subtracted, the difference of these normals provides a scale-based feature which
49
* can be further used to filter the point cloud, somewhat like the Difference of Guassians
50
* in image processing, but instead on surfaces. Best results are had when the two search
51
* radii are related as sigma_l=10*sigma_s, the octaves between the two search radii
52
* can be though of as a filter bandwidth. For appropriate values and thresholds it
53
* can be used for surface edge extraction.
54
*
55
* \attention The input normals given by setInputNormalsSmall and setInputNormalsLarge have
56
* to match the input point cloud given by setInputCloud. This behavior is different than
57
* feature estimation methods that extend FeatureFromNormals, which match the normals
58
* with the search surface.
59
*
60
* \note For more information please see
61
* <b>Yani Ioannou. Automatic Urban Modelling using Mobile Urban LIDAR Data.
62
* Thesis (Master, Computing), Queen's University, March, 2010.</b>
63
*
64
* \author Yani Ioannou.
65
* \ingroup features
66
*/
67
template
<
typename
Po
int
InT,
typename
Po
int
NT,
typename
Po
int
OutT>
68
class
DifferenceOfNormalsEstimation
:
public
Feature
<PointInT, PointOutT>
69
{
70
using
Feature
<PointInT, PointOutT>
::getClassName
;
71
using
Feature
<PointInT, PointOutT>
::feature_name_
;
72
using
PCLBase
<PointInT>
::input_
;
73
using
PointCloudN =
pcl::PointCloud<PointNT>
;
74
using
PointCloudNPtr =
typename
PointCloudN::Ptr
;
75
using
PointCloudNConstPtr =
typename
PointCloudN::ConstPtr
;
76
using
PointCloudOut =
typename
Feature<PointInT, PointOutT>::PointCloudOut
;
77
public
:
78
using
Ptr
= shared_ptr<DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT> >;
79
using
ConstPtr
= shared_ptr<const DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT> >;
80
81
/**
82
* Creates a new Difference of Normals filter.
83
*/
84
DifferenceOfNormalsEstimation
()
85
{
86
feature_name_
=
"DifferenceOfNormalsEstimation"
;
87
}
88
89
~DifferenceOfNormalsEstimation
()
90
{
91
//
92
}
93
94
/**
95
* Set the normals calculated using a smaller search radius (scale) for the DoN operator.
96
* @param normals the smaller radius (scale) of the DoN filter.
97
*/
98
inline
void
99
setNormalScaleSmall
(
const
PointCloudNConstPtr &normals)
100
{
101
input_normals_small_ = normals;
102
}
103
104
/**
105
* Set the normals calculated using a larger search radius (scale) for the DoN operator.
106
* @param normals the larger radius (scale) of the DoN filter.
107
*/
108
inline
void
109
setNormalScaleLarge
(
const
PointCloudNConstPtr &normals)
110
{
111
input_normals_large_ = normals;
112
}
113
114
/**
115
* Computes the DoN vector for each point in the input point cloud and outputs the vector cloud to the given output.
116
* @param output the cloud to output the DoN vector cloud to.
117
*/
118
void
119
computeFeature
(
PointCloudOut
&output)
override
;
120
121
/**
122
* Initialize for computation of features.
123
* @return true if parameters (input normals, input) are sufficient to perform computation.
124
*/
125
bool
126
initCompute
()
override
;
127
private
:
128
/** \brief Make the compute (&PointCloudOut); inaccessible from outside the class
129
* \param[out] output the output point cloud
130
*/
131
void
132
compute (
PointCloudOut
&) {}
133
134
///The smallest radius (scale) used in the DoN filter.
135
PointCloudNConstPtr input_normals_small_;
136
///The largest radius (scale) used in the DoN filter.
137
PointCloudNConstPtr input_normals_large_;
138
};
139
}
140
141
#ifdef PCL_NO_PRECOMPILE
142
#include <pcl/features/impl/don.hpp>
143
#endif
pcl::DifferenceOfNormalsEstimation::setNormalScaleLarge
void setNormalScaleLarge(const PointCloudNConstPtr &normals)
Set the normals calculated using a larger search radius (scale) for the DoN operator.
Definition
don.h:109
pcl::DifferenceOfNormalsEstimation::DifferenceOfNormalsEstimation
DifferenceOfNormalsEstimation()
Creates a new Difference of Normals filter.
Definition
don.h:84
pcl::DifferenceOfNormalsEstimation::initCompute
bool initCompute() override
Initialize for computation of features.
Definition
don.hpp:44
pcl::DifferenceOfNormalsEstimation::Ptr
shared_ptr< DifferenceOfNormalsEstimation< PointInT, PointNT, PointOutT > > Ptr
Definition
don.h:78
pcl::DifferenceOfNormalsEstimation::computeFeature
void computeFeature(PointCloudOut &output) override
Computes the DoN vector for each point in the input point cloud and outputs the vector cloud to the g...
Definition
don.hpp:85
pcl::DifferenceOfNormalsEstimation::~DifferenceOfNormalsEstimation
~DifferenceOfNormalsEstimation()
Definition
don.h:89
pcl::DifferenceOfNormalsEstimation::setNormalScaleSmall
void setNormalScaleSmall(const PointCloudNConstPtr &normals)
Set the normals calculated using a smaller search radius (scale) for the DoN operator.
Definition
don.h:99
pcl::DifferenceOfNormalsEstimation::ConstPtr
shared_ptr< const DifferenceOfNormalsEstimation< PointInT, PointNT, PointOutT > > ConstPtr
Definition
don.h:79
pcl::Feature::getClassName
const std::string & getClassName() const
Get a string representation of the name of this class.
Definition
feature.h:247
pcl::Feature::PointCloudOut
pcl::PointCloud< PointOutT > PointCloudOut
Definition
feature.h:124
pcl::Feature::feature_name_
std::string feature_name_
The feature name.
Definition
feature.h:223
pcl::Feature::Feature
Feature()
Empty constructor.
Definition
feature.h:131
pcl::PointCloudOut
pcl::PCLBase
PCL base class.
Definition
pcl_base.h:70
pcl::PCLBase< PointInT >::input_
PointCloudConstPtr input_
Definition
pcl_base.h:147
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition
point_cloud.h:173
pcl::PointCloud< PointNT >::Ptr
shared_ptr< PointCloud< PointNT > > Ptr
Definition
point_cloud.h:413
pcl::PointCloud< PointNT >::ConstPtr
shared_ptr< const PointCloud< PointNT > > ConstPtr
Definition
point_cloud.h:414
pcl
Definition
convolution.h:46