Abstract: An approach of color-texture image segmentation was proposed based on geodesic active contour model and multilayer graph cut model. As the clustering centers were commonly descripted with constant densities, the two phase Chan-vese model was extended to multiphase geodesic active contour model by using the Gaussian distribution to describe the changing density for each phase, and meanwhile the geodesic active contour was added into the proposed model, so that the presented approach could capture out the concave edge. For the minimization of the proposed energy function, a corresponded multilayer graph cut model was designed for resolving global approximated minimization by adopting maximum flow/minimum cut algorithm. Through the comparison experiment, the superiority of the proposed method can capture the concave boundary, which owns higher accuracy of the quantitative results.

Key words: color-texture, geodesic, active contours, image segmentation, multilayer graph cut model