In image retrieval systems, images can be represented by single feature vectors or by clouds of points. A cloud of points offers a more flexible description but suffers from class overlap. We propose a novel approach for describing clouds of points based on support vector data de
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In image retrieval systems, images can be represented by single feature vectors or by clouds of points. A cloud of points offers a more flexible description but suffers from class overlap. We propose a novel approach for describing clouds of points based on support vector data description (SVDD). We show that combining SVDD-based classifiers improves the retrieval precision. We investigate the performance of the proposed retrieval technique on a database of 368 texture images and compare it to other methods.@en