Shape retrieval by principal components descriptor

Authors:
Binhai Wang;Andrew J. Bangham;Yanong Zhu
Affiliations:
School of Computing Sciences, University of East Anglia, Norwich, UK;School of Computing Sciences, University of East Anglia, Norwich, UK;School of Computing Sciences, University of East Anglia, Norwich, UK
Venue:
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

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Abstract

Shape information is an important distribution to Content-Base Image Retrieval (CBIR) systems. There are two major types of shape descriptors, namely region-based and contour-based. In this paper we present a shape retrieval method that makes use of a contour-based descriptor, Principal Components Descriptor (PCD). In PCD, shapes are aligned on principal axes and described by a combination of the mean shape and weighted eigenvectors. The retrieval is achieved by comparing the weights of the eigenvectors. The developed approach is applied to Sharvit's Silhouettes database and the results are compared with MPEG-7 standard contour-based descriptor, Curvature Scale Space (CSS). The comparison indicates that PCD shows higher accuracy than CSS.