A Geometric Active Contours Model for Multiple Objects Segmentation

Authors:
Ning He;Peng Zhang;Ke Lu
Affiliations:
School of Mathematical Sciences, Capital Normal University, Beijing, China 100037;School of Mathematical Sciences, Capital Normal University, Beijing, China 100037;College of Computing & Communication Engineering, Graduate University of Chinese Academy of Sciences, Beijing, China 100049
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Year:
2008

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Abstract

The technique of geometric active contours has become quite popular for a variety of applications, particularly image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, can not be automatically handled. In this paper, we present an automatic geometric active contours model which can extract multiple objects in an image without any manual assistance and completely eliminates the need of costly re-initialization procedure. The proposed framework is inspired by the geodesic active contour model and leads to a paradigm that is relatively free from the initial curve position. According to the proposed flow, the traditional boundary attraction term is replaced with a new force that guides the propagation to the object boundaries from both sides. This new geometric active contour model is implemented using a level set approach, thereby allowing dealing naturally with topological changes.