Initialization Techniques for Segmentation with the Chan-Vese Model

Authors:
Jan Erik Solem;Niels Chr. Overgaard;Anders Heyden
Affiliations:
Malmo University, Sweden;Malmo University, Sweden;Malmo University, Sweden
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Year:
2006

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Abstract

This paper introduces an effective initialization approach for segmentation using the Chan-Vese model. The initial curve is found by searching among the extremals of the fidelity term, as a form of intelligent thresholding where the regularity of the threshold level is incorporated. The method has a nice connection to the curvature of the optimal initial partition boundary. The method is tested on several examples and gives considerable increase in performance.