A comprehensive image similarity retrieval system that utilizes multiple feature vectors in high dimensional space

Author

Curtis, K. ; Taniguchi, N. ; Nakagawa, J. ; Yamamuro, M.

Author_Institution

Database Syst. Lab., NTT Inf. & Commun. Syst. Labs., Kanagawa, Japan

Volume

1

fYear

1997

fDate

9-12 Sep 1997

Firstpage

180

Abstract

HyperMatch is a general purpose image retrieval engine made up of three components; a conventional database, a set of high dimensional image feature search indices and a coordinator. Various new and improved high dimensional indexing techniques are discussed for their applicability to different feature spaces and distance measurements. The role of the coordinator is to combine the search results from individual indices into an overall measure of similarity. Experiments reveal the coordinator must choose search parameters based on the number of features to be combined, data set size and the number of similar images requested. Important future development work includes index improvement and system evaluation

Keywords

feature extraction; image matching; indexing; query processing; visual databases; HyperMatch; coordinator; data set size; database; distance measurements; experiments; general purpose image retrieval engine; high dimensional image feature search indices; high dimensional indexing; high dimensional space; image similarity retrieval system; multiple feature vectors; search parameters; search results; Content based retrieval; Database systems; Engines; Extraterrestrial measurements; Image databases; Image retrieval; Indexing; Information retrieval; Laboratories; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on

Print_ISBN

0-7803-3676-3

Type

conf

DOI

10.1109/ICICS.1997.647083

Filename

647083