Abstract
In this note we will 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 to enforce spatial constraints among labels. © 2007 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Boccignone, G., Ferraro, M., & Napoletano, P. (2007). A variational bayes approach to image segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4729 LNCS, pp. 234–243). https://doi.org/10.1007/978-3-540-75555-5_22
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