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S. Conférences-nationales-gretsi-'05, S. Jehan-besson, A. Duner, M. Herbulot, G. Barlaud et al., Utilisation des gradients de forme et des contours actifs basés régions pour la segmentation des vecteurs mouvement, GRETSI conférence sur le traitement du signal et des images, 2005.

M. Autres-conférences, S. '04, A. Jehan-besson, M. Herbulot, G. Barlaud et al., Shape gradients for image and video segmentation, Mathematics and Image Analysis, 2003.

M. Barlaud and G. Aubert, Information theory for image segmentation using shape gradient, 2004.

. Dans-cette-thèse, sont pas toujours respectées et de considérer les distributions les plus "réelles" possible en utilisant une estimation non-paramétrique de ces distributions Nous présentons des critères issus de la théorie de l'information, comme l'entropie, an de segmenter des zones de faible variabilité dans les images. An de prendre en compte plusieurs canaux comme les canaux couleur, l'entropie jointe et l'information mutuelle sont aussi utilisées. Lorsqu'une information a priori est connue, la divergence de Kullback-Leibler permet d'introduire une notion de distance à une segmentation de référence en cherchant à minimiser une "distance" entre distributions. Enn, l'entropie jointe est utilisée an de segmenter des objets en, nous proposons de nous aranchir de ces hypothèses qui ne ou en estimant de façon conjointe le mouvement avec la segmentation