Dissimilarity measures for content-based image retrieval.
Hu, Rui; Ruger, Stefan; Song, Dawei; Liu, Haiming; Huang, Zi
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|
|Series Title||Proceedings of the IEEE international conference on multimedia and expo|
|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|
|Keywords||Dissimilarity measure; Feature space; Content based image retrieval|
HU 2008 Dissimilarity measures for content-based
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