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Dissimilarity measures for content-based image retrieval.

Hu, Rui; Ruger, Stefan; Song, Dawei; Liu, Haiming; Huang, Zi

Authors

Rui Hu

Stefan Ruger

Dawei Song

Haiming Liu

Zi Huang



Abstract

Dissimilarity measurement plays a crucial role in contentbased image retrieval. In this paper, sixteen core dissimilarity measures are introduced and evaluated. We carry out a systematic performance comparison on three image collections, including Corel, Getty and Trecvid2003, with seven different feature spaces. Two search scenarios are considered: single image queries based on Vector-Space-Model, and multiimage queries based on k-Nearest Neighbours search. A number of observations is drawn, which will lay a foundation for developing more effective image search technologies.

Start Date Jun 23, 2008
Publication Date Dec 31, 2008
Publisher Institute of Electrical and Electronics Engineers
Article Number 4607697
Pages 1365-1368
Series Title Proceedings of the IEEE international conference on multimedia and expo
ISBN 9781424425709
Institution Citation HU, R., RUGER, S., SONG, D., LIU, H. and HUANG, Z. 2008. Dissimilarity measures for content-based image retrieval. In Proceedings of the 2008 IEEE international conference on multimedia and expo (ICME 2008), 23-26 June 2008, Hannover, Germany. New York: IEEE [online], article number 4607697, pages 1365-1368. Available from: https://doi.org/10.1109/ICME.2008.4607697
DOI https://doi.org/10.1109/ICME.2008.4607697
Keywords Dissimilarity measure; Feature space; Content based image retrieval

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