In this paper, we discuss how image segmentation can be handled by using Bayesian learning and inference. In particular variational techniques relying on free energy minimization will be introduced. It will be shown how to embed a spatial diffusion process on segmentation labels within the Variational Bayes learning procedure so as to enforce spatial constraints among labels

Embedding Diffusion In Variational Bayes: a Technique for Segmenting Images. / G. BOCCIGNONE , M. FERRARO, P. NAPOLETANO. - In: INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE. - ISSN 0218-0014. - 22:5(2008 Aug), pp. 811-827.

Embedding Diffusion In Variational Bayes: a Technique for Segmenting Images.

G. BOCCIGNONE
Primo
;
2008

Abstract

In this paper, we discuss how image segmentation can be handled by using Bayesian learning and inference. In particular variational techniques relying on free energy minimization will be introduced. It will be shown how to embed a spatial diffusion process on segmentation labels within the Variational Bayes learning procedure so as to enforce spatial constraints among labels
Diffusion equation; Image segmentation; Model selection; Variational Bayes
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/53351
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