Active contours driven by the salient edge energy model.

In this brief, we present a new indicator, i.e., salient edge energy, for guiding a given contour robustly and precisely toward the object boundary. Specifically, we define the salient edge energy by exploiting the higher order statistics on the diffusion space, and incorporate it into a variational level set formulation with the local region-based segmentation energy for solving the problem of curve evolution. In contrast to most previous methods, the proposed salient edge energy allows the curve to find only significant local minima relevant to the object boundary even in the noisy and cluttered background. Moreover, the segmentation performance derived from our new energy is less sensitive to the size of local windows compared with other recently developed methods, owing to the ability of our energy function to suppress diverse clutters. The proposed method has been tested on various images, and experimental results show that the salient edge energy effectively drives the active contour both qualitatively and quantitatively compared to various state-of-the-art methods.