Abstract The Expectation Maximization (EM) algorithm and th e clustering method Fuzzy(C(Means (FCM) are widely used in image segmentation. However, the major drawback of these methods is their sensitivity to the noise. In this paper, we propose a variant of these methods which aim at resolving t his problem. Our approaches proceed by the characte rization of pixels by two features: the first one describes the intrinsic properties of the pixel and the second characteriz es the neighborhood of pixel. Then, the classification is made on the bas e on adaptive distance which privileges the one or the other features according to the spatial position of the pixel in t he image. The obtained results have shown a signifi cant improvement of our approaches performance compared to the standard ver sion of the EM and FCM, respectively, especially regarding about the robustness face to noise and the accuracy of the ed ges between regions.

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[17] Zadeh L., Fuzzy Sets, Information and Control , vol. 8, no. 3, pp. 338$353, 1965. Karim Kalti is an assistant professor in the Department of Computer Science of the Faculty of Science of Monastir, and member of research unit Sage (Advanced System in Electrical Engineeering) team signals, image and document National Engineering School of Sousse, University o f Sousse. His research interests include Computer vis ion, pattern recognition, medical imaging and data retri eval. He is a member of IEEE and his main results have been published in international journals and conferences. 18 The International Arab Journal of Information Technology, Vol. 11, No. 1, January 2014 Mohamed Mahjoub is an assistant professor in the Department of Computer Science and mathmatic at the Preparatory Institute of Engineering of Monastir and member of research unit Sage (Advanced System in Electrical Engineering), team signals, image and document National Engineering School of Sousse, University of Sousse. His research interests include dynamic bayesian network, computer vision, pattern recognition, HMM, and data retrieval. He is a member of IEEE and his main results have been published in international journals and conferences.