Robust active contour segmentation with an efficient global optimizer

Authors:
Jonas De Vylder;Jan Aelterman;Wilfried Philips
Affiliations:
Department of Telecommunications and Information Processing, IBBT - Image Processing and Interpretation, Ghent University, Ghent, Belgium;Department of Telecommunications and Information Processing, IBBT - Image Processing and Interpretation, Ghent University, Ghent, Belgium;Department of Telecommunications and Information Processing, IBBT - Image Processing and Interpretation, Ghent University, Ghent, Belgium
Venue:
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Year:
2011

Citing 11
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Abstract

Active contours or snakes are widely used for segmentation and tracking. Recently a new active contour model was proposed, combining edge and region information. The method has a convex energy function, thus becoming invariant to the initialization of the active contour. This method is promising, but has no regularization term. Therefore segmentation results of this method are highly dependent of the quality of the images. We propose a new active contour model which also uses region and edge information, but which has an extra regularization term. This work provides an efficient optimization scheme based on Split Bregman for the proposed active contour method. It is experimentally shown that the proposed method has significant better results in the presence of noise and clutter.