Sub-pixel precise edge localization: a ML approach based on color distributions
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
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In cluster-based segmentation pixels are mapped into various feature-spaces whereupon they are subjected to a grouping-algorithm. In this paper we develop a robust and versatile non-parametric clustering algorithm that is able to handle the unbalanced and irregular clusters encountered in such segmentation- applications.The strength of our approach lies in the definition and use of two cluster-validity indices that are independent of the cluster-topology. By combining them, an excellent clustering can be identified, and experiments confirm that the associated clusters do indeed correspond to perceptually salient image-regions.