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Prior-Based Piecewise-Smooth Segmentation by Template Competitive Deformation Using Partitions of Unity

Somphone, Oudom; Cohen, Laurent D.; Mory, Benoît; Makram-Ebeid, Sherif (2008), Prior-Based Piecewise-Smooth Segmentation by Template Competitive Deformation Using Partitions of Unity, dans Zisserman, Andrew, Computer Vision – ECCV 2008 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part III, Springer : Berlin Heidelberg, p. 628-641. 10.1007/978-3-540-88690-7_47

Type
Communication / Conférence
Lien vers un document non conservé dans cette base
https://hal.archives-ouvertes.fr/hal-00438799
Date
2008
Pays du colloque
FRANCE
Titre de l'ouvrage
Computer Vision – ECCV 2008 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part III
Auteurs de l’ouvrage
Zisserman, Andrew
Éditeur
Springer
Ville d’édition
Berlin Heidelberg
Isbn
978-3-540-88689-1
Pages
628-641
Identifiant publication
10.1007/978-3-540-88690-7_47
Métadonnées
Afficher la notice complète
Auteur(s)
Somphone, Oudom

Cohen, Laurent D.

Mory, Benoît

Makram-Ebeid, Sherif
Résumé (EN)
We propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. The image is segmented by a binary template that is deformed by a regular geometric transformation. The choice of the template together with the constraint on the transformation introduce the shape prior. The deformation is guided by the maximization of the likelihood of foreground and background intensity models, so that we can refer to this approach as Competitive Deformation. In each region, the intensity is modelled as a smooth approximation of the original image. We represent the transformation using a Partition of Unity Finite Element Method, which consists in representing each component with polynomial approximations within local patches. A conformity constraint between the patches provides a way to control the globality of the deformation. We show several results on synthetic images, as well as on medical data from different modalities.
Mots-clés
Competitive Deformation; shape prior; two-phase, piecewise-smooth segmentation

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