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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Image Segmentation Using Active Contours and Evidential Distance
verfasst von : Foued Derraz, Antonio Pinti, Miloud Boussahla, Laurent Peyrodie, Hechmi Toumi
Erschienen in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Verlag: Springer Berlin Heidelberg
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We proposed a new segmentation based on Active Contours (AC) for vector-valued image that incorporates evidential distance. The proposed method combine both Belief Functions (BFs) and probability functions in the Bhattacharyya distance framework. This formulation allows all features issued from vector-valued image and guide the evolution of AC using an inside/outside descriptor. The imprecision caused by the variation of the contrast issued from the multiple channels is incorporated in the BFs as weighted parameters. We demonstrated the performance of the proposed algorithm using some challenging color biomedical images.