![]() |
ITK
4.2.0
Insight Segmentation and Registration Toolkit
|
Collaboration diagram for Module ITKConnectedComponents:Classes | |
| class | itk::ConnectedComponentFunctorImageFilter< TInputImage, TOutputImage, TFunctor, TMaskImage > |
| A generic connected components filter that labels the objects in an artibitrary image. More... | |
| class | itk::ConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage > |
| Label the objects in a binary image. More... | |
| class | itk::HardConnectedComponentImageFilter< TInputImage, TOutputImage > |
| class | itk::RelabelComponentImageFilter< TInputImage, TOutputImage > |
| Relabel the components in an image such that consecutive labels are used. More... | |
| class | itk::ScalarConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage > |
| A connected components filter that labels the objects in an arbitrary image. Two pixels are similar if they are within threshold of each other. Uses ConnectedComponentFunctorImageFilter. More... | |
| class | itk::Functor::SimilarVectorsFunctor< TInput > |
| A connected components filter that labels the objects in a vector image. Two vectors are pointing similar directions if one minus their dot product is less than a threshold. Vectors that are 180 degrees out of phase are similar. Assumes that vectors are normalized. More... | |
| class | itk::ThresholdMaximumConnectedComponentsImageFilter< TInputImage, TOutputImage > |
| Finds the threshold value of an image based on maximizing the number of objects in the image that are larger than a given minimal size. More... | |
| class | itk::VectorConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage > |
| A connected components filter that labels the objects in a vector image. Two vectors are pointing similar directions if one minus their dot product is less than a threshold. Vectors that are 180 degrees out of phase are similar. Assumes that vectors are normalized. More... | |
This module contains modules to identify and modify connected components. Theses algorithms are commonly applied to binary or label map images. See also Module ITKClassifiers, Module ITKLabelMap, and Module ITKBinaryMathematicalMorphology.
1.8.1