Fast finsler active contours and shape prior descriptor

Authors:
Foued Derraz;Abdelmalik Taleb-Ahmed;Laurent Peyrodie;Gerard Forzy;Christina Boydev
Affiliations:
Faculté Libre de Médecine, Lille, France;LAMIH FRE CNRS 3036, Université de Valenciennes, Valenciennes, France;HEI - Hautes Etudes d'Ingénieur, Lille, France;Faculté Libre de Médecine, Lille, France;Faculté Libre de Médecine, Lille, France
Venue:
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2011

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Abstract

In this paper we proposed a new segmentation method based Fast Finsler Active Contours (FFAC). The FFAC is formulated in the Total Variation (TV) framework incorporating both region and shape descriptors. In the Finsler metrics, the anisotropic boundary descriptor favorites strong edge locations and suitable directions aligned with dark to bright image gradients. Strong edges are not required everywhere along. We prove the existence of a solution to the new binary Finsler active contours model and we propose a fast and easy algorithm in characteristic function framework. Finally, we show results on some MR challenging images to illustrate accurate.