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Proceedings Paper

An effective and simple relevance feedback algorithm for image retrieval
Author(s): Na Yang; Xiangyang Xue
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Paper Abstract

Relevance feedback in content-based image retrieval has been an active research focus for many years. It uses user-labeled information to re-adjust the measurement of similarity between images to get the improved retrieval results. In this paper we propose a simple and effective approach for image relevance feedback, which uses both positive and negative examples labeled by users to refine the query and update the distance measurement dynamically. Our method not only has a very low complexity but also adapts well to the changes of user’s retrieval interests. Experimental results on a database of 7,000 images represented by MPEG-7 color and texture descriptors show the efficiency of our algorithm compared with other two existing algorithms.

Paper Details

Date Published: 10 January 2003
PDF: 10 pages
Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); doi: 10.1117/12.476246
Show Author Affiliations
Na Yang, Fudan Univ. (China)
Xiangyang Xue, Fudan 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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