An approach for image segmentation is introduced based on region segmentation and edge detection.Edges are first detected in the original image and then cut equidistantly into some segmentations,and the end points of segmentations are gathered into a points set.A constrained Delaunay triangulation is yielded from the points set and then a graph is attained too.Graph cut,Minimum Spanning Tree(MST),is performed.Finally,the obtained regions are projected into the original image and region boundaries are refined to achieve pixel accuracy by Snake model.Experimental results show that the approach can achieve accurate edge localization,better spatial coherence and improved efficiency.