and its application to the image segmentation problem is demonstrated.An important characteristic of the criterion is that in the course of image segmentation the local and global image segmentation information is fused together.Moreover
optimizing weighted cut can ensure that the inter-cluster similarity is minimized while intra-cluster similarity is maximized.We show that an efficient computational technique based on an eigenvector problem can be used to optimize this criterion.The experimental results on a number of artificial point sets and real-world images show the effectiveness of the new criterion.