Variational Framework for Probabilistic Image Segmentation: Theory and Applications - Oscar S. Dalmau Cedeño - Livros - LAP LAMBERT Academic Publishing - 9783659219016 - 24 de agosto de 2012
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Variational Framework for Probabilistic Image Segmentation: Theory and Applications

Oscar S. Dalmau Cedeño

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Variational Framework for Probabilistic Image Segmentation: Theory and Applications

Image segmentation is an important field of image processing. It consists in partitioning the image into non-overlapping meaningful homogenous regions i.e. flat regions, movement (stereo, optical flow), model-based, texture, color, ... etc. This has been widely used in different applications, for instance, medical images and robot vision. This work focuses on two main themes. The first is related with image segmentation problem and the second is about an application of segmentation methods to image and video editing. In the last decade especial attention has been paid to segmentation methods that produce a measure of belonging to classes, instead of classical segmentation methods that obtains a label map. The first kind of methods is known in the literature as ?soft? segmentation methods while the second group is called as ?hard? segmentation methods. This work presents a general framework for ?soft? segmentation with spatial coherence through a Markov Random Field prior.

Mídia Livros     Paperback Book   (Livro de capa flexível e brochura)
Lançado 24 de agosto de 2012
ISBN13 9783659219016
Editoras LAP LAMBERT Academic Publishing
Páginas 260
Dimensões 150 × 15 × 226 mm   ·   405 g
Idioma German