A novel algorithm for relevance feedback in region-based image retrieval system

Xiao Peng; Shaoping Ma; Zhong Su; Liyun Ru

doi:10.1117/12.476254

10 January 2003 Novel algorithm in relevance feedback in region-based image retrieval system

Xiao Peng, Shaoping Ma, Zhong Su, Liyun Ru

Author Affiliations +

Proceedings Volume 5021, Storage and Retrieval for Media Databases 2003; (2003) https://doi.org/10.1117/12.476254
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

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.

Citation Download Citation

Xiao Peng, Shaoping Ma, Zhong Su, and Liyun Ru "Novel algorithm in relevance feedback in region-based image retrieval system", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.476254

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