A novel region-based active contour approach relying on local and lobal information

This paper proposes a novel approach that allows region-based active contour energy to be re-expressed combining local and global information. The basic idea of this technique consists in extracting image statistics locally from the heterogeneous region (foreground or background) and globally from the other region at each point along the curve. By exploiting benefits of both local-based and global-based statistics, this technique proves to be robust against heterogeneity and noise and shows low sensitivity to curve initialization. Experimental results for synthetic and real images reveal significant improvement compared to conventional methods.