A mean based graph theoretic approach for image segmentation

This paper presents a new mean based graph theoretic approach for image segmentation. The proposed method which is capable of accurately locating region boundaries has the following salient features. First, it is a non-supervised approach which reflects the non-local properties of the image. Second, it guarantees that the regions are connected. Finally, it produces robust results which are almost unaffected by the influences of outliers. In this technique, the merging of regions is carried out based on the mean of the intermediate edges and edges within each region.