18 #ifndef __itkScalarImageKmeansImageFilter_h
19 #define __itkScalarImageKmeansImageFilter_h
62 template<
typename TInputImage,
63 typename TOutputImage = Image< unsigned char, TInputImage::ImageDimension > >
70 TInputImage::ImageDimension);
136 itkSetMacro(UseNonContiguousLabels,
bool);
137 itkGetConstReferenceMacro(UseNonContiguousLabels,
bool);
138 itkBooleanMacro(UseNonContiguousLabels);
147 #ifdef ITK_USE_CONCEPT_CHECKING
188 #ifndef ITK_MANUAL_INSTANTIATION
189 #include "itkScalarImageKmeansImageFilter.hxx"
static const unsigned int ImageDimension
void operator=(const Self &)
void PrintSelf(std::ostream &os, Indent indent) const
itk::Statistics::MinimumDecisionRule DecisionRuleType
ScalarImageKmeansImageFilter()
fast k-means algorithm implementation using k-d tree structure
NumericTraits< InputPixelType >::RealType RealPixelType
itk::Statistics::ImageToListSampleAdaptor< InputImageType > AdaptorType
InputImageType::RegionType ImageRegionType
MeansContainer m_InitialMeans
An image region represents a structured region of data.
bool m_ImageRegionDefined
SmartPointer< Self > Pointer
Base class for all process objects that output image data.
Superclass::KdTreeType KdTreeType
A decision rule that returns the class label with the smallest discriminant score.
bool m_UseNonContiguousLabels
ClassifierType::MembershipFunctionVectorType MembershipFunctionVectorType
InputImageType::PixelType InputPixelType
ImageRegionType m_ImageRegion
std::vector< RealPixelType > MeansContainer
itk::Statistics::KdTreeBasedKmeansEstimator< TreeType > EstimatorType
This class generates a KdTree object with centroid information.
itk::Statistics::DistanceToCentroidMembershipFunction< MeasurementVectorType > MembershipFunctionType
Sample classification class.
virtual void VerifyPreconditions()
Verifies that the process object has been configured correctly, that all required inputs are set...
MeasurementPixelTraitsType::MeasurementVectorType MeasurementVectorType
void SetImageRegion(const ImageRegionType ®ion)
std::vector< MembershipFunctionPointer > MembershipFunctionVectorType
itk::Statistics::SampleClassifierFilter< AdaptorType > ClassifierType
TOutputImage OutputImageType
TInputImage InputImageType
TInputImage InputImageType
ScalarImageKmeansImageFilter Self
OutputImageType::PixelType OutputPixelType
TreeGeneratorType::KdTreeType TreeType
Classifies the intensity values of a scalar image using the K-Means algorithm.
ClassifierType::ClassLabelVectorType ClassLabelVectorType
SmartPointer< const Self > ConstPointer
Extract a region of interest from the input image.
RegionOfInterestImageFilter< InputImageType, InputImageType > RegionOfInterestFilterType
DistanceToCentroidMembershipFunction models class membership using a distance metric.
virtual ~ScalarImageKmeansImageFilter()
std::vector< ClassLabelType > ClassLabelVectorType
Base class for filters that take an image as input and produce an image as output.
Control indentation during Print() invocation.
void AddClassWithInitialMean(RealPixelType mean)
ImageToImageFilter< InputImageType, OutputImageType > Superclass
Define additional traits for native types such as int or float.
This class provides ListSample interface to ITK Image.
#define itkConceptMacro(name, concept)
EstimatorType::ParametersType ParametersType
AdaptorType::MeasurementVectorType MeasurementVectorType
MembershipFunctionType::CentroidType MembershipFunctionOriginType
itk::Statistics::WeightedCentroidKdTreeGenerator< AdaptorType > TreeGeneratorType
ParametersType m_FinalMeans
MembershipFunctionType::Pointer MembershipFunctionPointer