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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkSampleClassifier.h,v $
Language: C++
Date: $Date: 2009-03-04 19:29:53 $
Version: $Revision: 1.17 $
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 __itkSampleClassifier_h
#define __itkSampleClassifier_h
#include <vector>
#include "itkObject.h"
#include "itkExceptionObject.h"
#include "itkSubsample.h"
#include "itkMembershipSample.h"
#include "itkClassifierBase.h"
namespace itk {
namespace Statistics {
/** \class SampleClassifier
* \brief Integration point for MembershipCalculator, DecisionRule, and
* target sample data.
*
* The first template argument is the type of the target sample data
* that this classifier will assign a class label for each measurement
* vector. The second one is the type of a membership value calculator
* for each. A membership calculator represents a specific knowledge about
* a class. In other words, it should tell us how "likely" is that a
* measurement vector (pattern) belong to the class. The third argument
* is the type of decision rule. The main role of a decision rule is
* comparing the return values of the membership calculators. However,
* decision rule can include some prior knowledge that can improve the
* result.
*
* Before you call the GenerateData method to start the classification process,
* you should plug in all necessary parts ( one or more membership
* calculators, a decision rule, and a target sample data). To plug in
* the decision rule, you use SetDecisionRule method, for the target sample
* data, SetSample method, and for the membership calculators, use
* AddMembershipCalculator method.
*
* As the method name indicates, you can have more than one membership
* calculator. One for each classes. The order you put the membership
* calculator becomes the class label for the class that is represented
* by the membership calculator.
*
* The classification result is stored in a vector of Subsample object.
* Each class has its own class sample (Subsample object) that has
* InstanceIdentifiers for all measurement vectors belong to the class.
* The InstanceIdentifiers come from the target sample data. Therefore,
* the Subsample objects act as separate class masks.
*
* <b>Recent API changes:</b>
* The static const macro to get the length of a measurement vector,
* \c MeasurementVectorSize has been removed to allow the length of a measurement
* vector to be specified at run time. Please use the function
* GetSample().GetMeasurementVectorSize() instead.
*
*/
template< class TSample >
class ITK_EXPORT SampleClassifier :
public ClassifierBase< TSample >
{
public:
/** Standard class typedefs */
typedef SampleClassifier Self;
typedef ClassifierBase< TSample > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Standard macros */
itkTypeMacro(SampleClassifier, Object);
itkNewMacro(Self);
/** Output type for GetClassSample method */
typedef MembershipSample< TSample > OutputType;
/** typedefs from TSample object */
typedef typename TSample::MeasurementType MeasurementType;
typedef typename TSample::MeasurementVectorType MeasurementVectorType;
/** typedefs from Superclass */
typedef typename Superclass::MembershipFunctionPointerVector
MembershipFunctionPointerVector;
typedef unsigned int ClassLabelType;
typedef std::vector< ClassLabelType > ClassLabelVectorType;
/** Sets the target data that will be classified by this */
void SetSample(const TSample* sample);
/** Returns the target data */
const TSample* GetSample() const;
/** Sets the user given class labels for membership functions.
* If users do not provide class labels for membership functions by calling
* this function, then the index of the membership function vector for a
* membership function will be used as class label of measurement vectors
* belong to the membership function */
void SetMembershipFunctionClassLabels( ClassLabelVectorType& labels);
/** Gets the user given class labels */
ClassLabelVectorType& GetMembershipFunctionClassLabels()
{ return m_ClassLabels; }
/** Returns the classification result */
OutputType* GetOutput();
protected:
SampleClassifier();
virtual ~SampleClassifier() {}
void PrintSelf(std::ostream& os, Indent indent) const;
/** Starts the classification process */
void GenerateData();
private:
/** Target data sample pointer */
const TSample* m_Sample;
/** Output pointer (MembershipSample) */
typename OutputType::Pointer m_Output;
/** User given class labels for membership functions */
ClassLabelVectorType m_ClassLabels;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkSampleClassifier.txx"
#endif
#endif
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