Pixel Classification Filters
[Intensity-Based Image Segmentation Filters]

Collaboration diagram for Pixel 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, TOutputImage >
	Classifies the intensity values of a scalar image using the K-Means algorithm. More...
Modules
	Supervised Classification Filters
	Unsupervised 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.