Efficient retrieval for browsing large image databases

Daniel Wu, Divyakant Agrawal, Amr El Abbadi, Ambuj Singh, Terrence R. Smith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Citations (Scopus)

Abstract

The Alexandria project has been initiated to build a digital library for map and satellite images. Designed for content-based retrieval, the relevant information in each image is encoded in the form of a multi-dimensional feature vector. Though representing images by feature vectors greatly facilitates user queries, indexing these vectors degrades performance when the number of dimensions is large. We consider 2 popular techniques (DFT and SVD) to reduce the dimension of feature vectors, and study their retrieval performance with respect to recall and precision. We find that though SVD generally out-performs DFT, DFT compares favorably in a limited range suitable for browsing large image databases.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
EditorsK. Barker, M.T. Ozsu
Pages11-18
Number of pages8
Publication statusPublished - 1 Dec 1996
Externally publishedYes
EventProceedings of the 1996 5th ACM CIKM International Conference on Information and Knowledge Management - Rockville, MD, USA
Duration: 12 Nov 199616 Nov 1996

Other

OtherProceedings of the 1996 5th ACM CIKM International Conference on Information and Knowledge Management
CityRockville, MD, USA
Period12/11/9616/11/96

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ASJC Scopus subject areas

  • Business, Management and Accounting(all)

Cite this

Wu, D., Agrawal, D., El Abbadi, A., Singh, A., & Smith, T. R. (1996). Efficient retrieval for browsing large image databases. In K. Barker, & M. T. Ozsu (Eds.), International Conference on Information and Knowledge Management, Proceedings (pp. 11-18)