Dissimilarity measures for content-based image retrieval

Rui Hu*, Stefan Rüger, Dawei Song, Haiming Liu, Zi Huang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

34 Citations (Scopus)

Abstract

Dissimilarity measurement plays a crucial role in content-based image retrieval. In this paper, 16 core dissimilarity measures are introduced and evaluated. We carry out a systematic performance comparison on three image collections, Corel, Getty and Trecvid2003, with 7 different feature spaces. Two search scenarios are considered: single image queries based on the Vector Space Model, and multi-image queries based on k-Nearest Neighbours search. A number of observations are drawn, which will lay a foundation for developing more effective image search technologies.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings
Pages1365-1368
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Hannover, Germany
Duration: 23 Jun 200826 Jun 2008

Publication series

Name2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings

Conference

Conference2008 IEEE International Conference on Multimedia and Expo, ICME 2008
Country/TerritoryGermany
CityHannover
Period23/06/0826/06/08

Keywords

  • Content-based image retrieval
  • Dissimilarity measure
  • Feature space

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