On fitting finite dirichlet mixture using ECM and MML

Authors:
Nizar Bouguila;Djemel Ziou
Affiliations:
Université de Sherbrooke, Sherbrooke, Qc, Canada;Université de Sherbrooke, Sherbrooke, Qc, Canada
Venue:
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Year:
2005

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Abstract

Gaussian mixture models are being increasingly used in pattern recognition applications. However, for a set of data other distributions can give better results. In this paper, we consider Dirichlet mixtures which offer many advantages [1]. The use of the ECM algorithm and the minimum message length (MML) approach to fit this mixture model is described. Experimental results involve the summarization of texture image databases.