Dealing with Segmentation Errors in Region-based Stereo Matching Ángeles López, Filiberto Pla

Graph-based matching methods have been widely used in the areas of object recognition and stereo correspondence. In this paper, an algorithm to deal with segmentation errors in region-based matching is proposed, which consists of a preprocessing stage to the classical graph-based matching algorithm. Some regions are merged and included in the matching process in order to avoid the differences in segmentation. The selection of an appropriate similarity criterion to create the initial nodes in the graph and the use of approximative algorithms to find maximal cliques are important issues in order to reduce the computational burden. The experimental results show that the method is robust enough in the presence of noise. Keywords: Region matching, segmentation errors, graph-based matching, maximal cliques, stereo vision.