Abstract
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.
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Lai, C., Tax, D.M.J., Duin, R.P.W., Pękalska, E., Paclík, P. (2002). On Combining One-Class Classifiers for Image Database Retrieval. In: Roli, F., Kittler, J. (eds) Multiple Classifier Systems. MCS 2002. Lecture Notes in Computer Science, vol 2364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45428-4_21
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DOI: https://doi.org/10.1007/3-540-45428-4_21
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