Abstract
We propose a novel statistical approach for color texture modeling and classification based on Co-occurrence matrices and discrete finite mixture models. Our statistical model assigns relevance weights to discrete Co-occurrence features that are considered as random variables. Experimental results are presented to illustrate the merits of our approach on a difficult problem which is the categorization of the well-known Vistex color texture images database.
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