A Robust Graph Theoretic Approach for Image Segmentation

This paper presents a new robust 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 is almost unaffected by the influences of outliers. In thistechnique, at each step, a minimum weight edge is selected and the two regions connected by the minimum weight edge are considered for merge. The merging of regions is carried out, if the mean of the edges connecting the two regions is smaller than the maximum of the mean of the intra region edges along with the threshold value.