Noise-free similarity model for image retrieval systems

Khanh Vu; Kien A. Hua; JungHwan Oh

doi:10.1117/12.410917

1 January 2001 Noise-free similarity model for image retrieval systems

Khanh Vu, Kien A. Hua, JungHwan Oh

Proceedings Volume 4315, Storage and Retrieval for Media Databases 2001; (2001) https://doi.org/10.1117/12.410917
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

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.

Citation Download Citation

Khanh Vu, Kien A. Hua, and JungHwan Oh "Noise-free similarity model for image retrieval systems", Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); https://doi.org/10.1117/12.410917

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