1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkSampleMeanShiftClusteringFilter.h,v $
Language: C++
Date: $Date: 2009-03-04 19:29:54 $
Version: $Revision: 1.5 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkSampleMeanShiftClusteringFilter_h
#define __itkSampleMeanShiftClusteringFilter_h
#include <vector>
#include "itkSampleAlgorithmBase.h"
namespace itk {
namespace Statistics {
/** \class SampleMeanShiftClusteringFilter
* \brief This filter create a cluster map from an input sample.
*
* The clustering process is done by linking measurement vectors whose
* distance is below the threshold value set by the SetThreshold
* method. However, if the resulting cluster size is below the minimum
* number of measurement vectors set by the MinimumClusterSize
* method. Such measurement vectors are clustered together and
* labelled zero.
*
* \sa SampleMeanShiftBlurringFilter, SampleSelectiveMeanShiftBlurringFilter
*/
template< class TSample >
class SampleMeanShiftClusteringFilter :
public SampleAlgorithmBase< TSample >
{
public:
/** Standard class typedefs. */
typedef SampleMeanShiftClusteringFilter Self;
typedef SampleAlgorithmBase< TSample > Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Standard Macros */
itkTypeMacro(SampleMeanShiftClusteringFilter,
SampleAlgorithmBase);
itkNewMacro(Self);
typedef typename TSample::MeasurementVectorType MeasurementVectorType;
typedef typename TSample::MeasurementType MeasurementType;
typedef typename TSample::InstanceIdentifier InstanceIdentifier;
typedef std::vector< InstanceIdentifier > SearchResultVectorType;
typedef std::vector< int > ClusterLabelsType;
itkSetMacro(Threshold, double);
itkGetMacro(Threshold, double);
itkSetMacro(MinimumClusterSize, unsigned long);
itkGetMacro(MinimumClusterSize, unsigned long);
ClusterLabelsType& GetOutput()
{ return m_Output; }
protected:
SampleMeanShiftClusteringFilter();
virtual ~SampleMeanShiftClusteringFilter();
void PrintSelf(std::ostream& os, Indent indent) const;
void GenerateData();
private:
double m_Threshold;
ClusterLabelsType m_Output;
MeasurementVectorType m_TempQueryPoint;
SearchResultVectorType m_TempSearchResult;
unsigned long m_MinimumClusterSize;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkSampleMeanShiftClusteringFilter.txx"
#endif
#endif
|
