A Markov random field model for mode detection in cluster analysis

Authors:
Ahmed Moussa;Abderrahmane Sbihi;Jack-Gérard Postaire
Affiliations:
Université Abd-Elmalek Assaadi, ENSAT, BP1818 Tanger, Morocco;Université Ibn Tofail, Faculté des Sciences, LIRF, BP133 Kenitra, Morocco;Université des Sciences et Technologies de Lille, LAGIS and IUT "A", 59655 Villeneuve d'Ascq Cedex, France
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

A statistical clustering approach is proposed, based on Markov random field models. A discrete field derived from the raw data set is considered as a field of measures. A hidden field, computed using a new potential function, is used to detect the modes that correspond to domains of high local concentrations of observations. Results obtained on artificially generated and real data sets demonstrate the efficiency of this new approach for unsupervised pattern classification.