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
94
95
96
97
98
99
100
101
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkMaximumRatioDecisionRule.h
Language: C++
Date: $Date$
Version: $Revision$
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 __itkMaximumRatioDecisionRule_h
#define __itkMaximumRatioDecisionRule_h
#include "itkWin32Header.h"
#include <vector>
#include "vnl/vnl_matrix.h"
#include "itkNumericTraits.h"
#include "itkDecisionRuleBase.h"
namespace itk {
/** \class MaximumRatioDecisionRule
* \brief This rule returns \f$i\f$ if
* \f$\frac{f_{i}(\overrightarrow{x})}{f_{j}(\overrightarrow{x})} >
* \frac{K_{j}}{K_{i}}\f$ for all \f$j \not= i\f$,
* where the \f$i\f$ is the index of a class which has
* membership function \f$f_{i}\f$ and its prior value
* (usually, the a priori probability or the size of a class) is
* \f$K_{i}\f$
*
* Users should set the a priori values before calling the Evaluate method.
*
* \sa MaximumDecisionRule, MinimumDecisionRule
*/
class ITKCommon_EXPORT MaximumRatioDecisionRule :
public DecisionRuleBase
{
public:
/** Standard class typedefs */
typedef MaximumRatioDecisionRule Self;
typedef DecisionRuleBase Superclass;
typedef SmartPointer<Self> Pointer;
/** Run-time type information (and related methods) */
itkTypeMacro(MaximumRatioDecisionRule, DecisionRuleBase);
/** Standard New() method support */
itkNewMacro(Self);
typedef float APrioriValueType;
typedef std::vector< APrioriValueType > APrioriVectorType;
typedef APrioriVectorType::size_type APrioriVectorSizeType;
/** Types for the arguments that are acceptable in the Evaluate() method */
typedef Superclass::VectorType VectorType;
typedef Superclass::ArrayType ArrayType;
/** The return value of this function is a class label.
* Basically, using its internal logic based on the discriminant
* scores, this function decides best class label and return it.
*/
virtual unsigned int Evaluate( const VectorType &discriminantScores) const;
/** The return value of this function is a class label.
* Basically, using its internal logic based on the discriminant
* scores, this function decides best class label and return it.
*/
virtual unsigned int Evaluate( const ArrayType &discriminantScores) const;
/** Sets the a priori probabilities */
void SetAPriori(APrioriVectorType& values);
protected:
MaximumRatioDecisionRule();
virtual ~MaximumRatioDecisionRule() {}
private:
MaximumRatioDecisionRule(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
/** Number of classes */
APrioriVectorSizeType m_NumberOfClasses;
/** a priori probability ratio matrix: internal use */
vnl_matrix< double > m_APrioriRatioMatrix;
}; // end of class
} // end of namespace
#endif
|
