Pixel Classification Filters
[Intensity-Based Image Segmentation Filters]

Collaboration diagram for Pixel Classification Filters:

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Detailed Description

Pixel classification filters use statistical classification algorithms to assign a label to a given image pixel. Classification algorithms can be supervised when training data is available or unsupervised when no training data is available.

Modules
	Supervised Classification Filters
	Unsupervised Classification Filters
Classes
class	itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >
	Performs Bayesian Classification on an image. More...
class	itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >
	This filter is intended to be used as a helper class to initialize the BayesianClassifierImageFilter. The goal of this filter is to generate a membership image that indicates the membership of each pixel to each class. These membership images are fed as input to the bayesian classfier filter. More...
class	itk::ClassifierBase< TDataContainer >
	Base class for classifier object. More...
class	itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >
	Base class for ImageGaussianModelEstimator object. More...
class	itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >
	Base class for ImageKmeansModelEstimator object. More...
class	itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
	Base class for model estimation from images used for classification. More...
class	itk::ScalarImageKmeansImageFilter< TInputImage >
	Classifies the intensity values of a scalar image using the K-Means algorithm. More...

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