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Pixel Classification Filters
[Intensity-Based Image Segmentation Filters]

Collaboration diagram for Pixel Classification Filters:

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.


 Supervised Classification Filters
 Unsupervised Classification Filters


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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