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Advances in Mathematical Physics
Volume 2013 (2013), Article ID 501628, 7 pages
Research Article

A Fast Region-Based Segmentation Model with Gaussian Kernel of Fractional Order

College of Mathematics and Computational Science, Shenzhen University, Shenzhen 518060, China

Received 11 August 2013; Revised 3 September 2013; Accepted 3 September 2013

Academic Editor: Ming Li

Copyright © 2013 Bo Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


By summarizing some classical active contour models from the view of level set representation, a simple energy function expression with the Gaussian kernel of fractional order is proposed, and then a novel region-based geometric active contour model is established. In this proposed model, the energy function with value of [−1, 1] is built, the local mean and global mean of the inside and outside of the evolution curve are employed, and the segmentation results are obtained by controlling the expansion and contraction of the evolution curve. The model is simple and easy to implement; it can also protect weak edges because of considering more statistical information. Experimental results on synthetic and natural images show that the proposed model is much more effective in dealing with the images with weak or blurred edges, and it takes less time.