In this paper, we present a new theory regarding cluster overlap, which allows for the computation of a cluster overlap rate that turns out being a very good measure of similarity between clusters. Using this measure, we also develop a new hierarchical algorithm for image segmentation that partially solves the problem of determining the best number of clusters. Experimental results demonstrate the effectiveness of the overlap rate measuring method and the new hierarchical clustering algorithm.
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