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Proceedings Paper

Noise-free similarity model for image retrieval systems
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Paper Abstract

Reducing noise in image query processing is no doubt one of the key elements to achieve high retrieval effectiveness. However, existing techniques are not able to eliminate noise from similarity matching since they capture the features of the entire image are or pre-perceived objects at the database build time. In this paper we address this outstanding issue by proposing a similarity mode for noise- free queries. In our approach, users formulate their queries by specifying objects of interest, and image similarity is based only on these relevant objects. We discuss how our approach can handle translation and scaling matching as well as how space overhead can be minimized. Our experiments show that this approach, with 1/16 the storage overhead, outperforms techniques for rectangular queries and a related technique by a significant margin.

Paper Details

Date Published: 1 January 2001
PDF: 11 pages
Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); doi: 10.1117/12.410917
Show Author Affiliations
Khanh Vu, Univ. of Central Florida (United States)
Kien A. Hua, Univ. of Central Florida (United States)
JungHwan Oh, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 4315:
Storage and Retrieval for Media Databases 2001
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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