Image segmentation under occlusion using selective shape priors

Authors:
Huang Fuzhen;Yang Xuhong
Affiliations:
Department of Information & Control Engineering, Shanghai University of Electric Power, Shanghai, China;Department of Information & Control Engineering, Shanghai University of Electric Power, Shanghai, China
Venue:
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Year:
2010

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Abstract

In this paper a new method using selective shape priors in a level set framework for image segmentation under occlusion is presented. To solve occluded boundaries, prior knowledge of shape of objects is introduced using the Nitzberg-Mumford-Shiota variational formulation within the segmentation energy. The novelty of our model is that the use of shape prior knowledge is automatically restricted only to occluded parts of the object boundaries. Experiments on synthetic and real image segmentation show the efficiency of our method.