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Proceedings Paper

A novel algorithm for relevance feedback in region-based image retrieval system
Author(s): Xiao Peng; Shaoping Ma; Zhong Su; Liyun Ru
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Paper Abstract

This paper proposes an algorithm for relevance feedback in region-based image retrieval systems. In region-based image retrieval systems one image usually represented by many regions, each region is represented by a feature vector. Because traditional region-based feedback algorithms are based on the one-vector model, it is hard to directly use past feedback algorithms to a region-based image retrieval system. In this paper we propose a novel feedback algorithm using clustering among regions in all feedback images on region-based image retrieval systems. All regions in one image are divided into two parts: the foreground regions and the background regions based on the feedback images. Here foreground regions stand for the common property of all feedback images, which can be viewed as being of one semantic category. The others are background regions, which may stand for different semantic categories. During feedback, we treat the two kinds of regions with different manner. Experimental results show that using such algorithm improves the retrieval performance of region based image system.

Paper Details

Date Published: 10 January 2003
PDF: 8 pages
Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); doi: 10.1117/12.476254
Show Author Affiliations
Xiao Peng, Tsinghua Univ. (China)
Shaoping Ma, Tsinghua Univ. (China)
Zhong Su, Tsinghua Univ. (China)
Liyun Ru, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 5021:
Storage and Retrieval for Media Databases 2003
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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