On combining one-class classifiers for image database retrieval

Conference paper (2002)

Authors

C Lai External organisation
D.M.J. Tax ImPhys/Quantitative Imaging
R.P.W. Duin ImPhys/Quantitative Imaging
E.M. Pekalska ImPhys/Quantitative Imaging
P. Paclik ImPhys/Quantitative Imaging
Research Group
ImPhys/Quantitative Imaging
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Published Date

2002

Language

Undefined/Unknown

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Research Group

ImPhys/Quantitative Imaging

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.