AN EFFICIENT CLUSTERING-ALGORITHM FOR REGION MERGING

This paper proposes an efficient clustering algorithm for region mergi ng. To speed up the search of the best pair of regions which is merged into one region, dissimilarity values of all possible pairs of region s are stored in a heap. Then the best pair can be found as the element of the root node of the binary tree corresponding to the heap. Since only adjacent pairs of regions are possible to be merged in image segm entation, this constraints of neighboring relations are represented by sorted linked lists. Then we can reduce the computation for updating the dissimilarity values and neighboring relations which are influence d by the merging of the best pair. The proposed algorithm is applied t o the segmentations of a monochrome image and range images.