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This paper describes a new probabilistic framework for recognizing textures in images. Images are described by local affine-invariant descriptors and their spatial relationships. We introduce a statistical parametric models of the dependence between descriptors. We use Hidden Markov Models (HMM) and estimate the parameters with a recent technique based on the mean field principle. Preliminary results for texture recognition are promising and outperform existing techniques.

Markov random fields for textures recognition with local invariant regions and their geometric relationships