Approximate Query Processing for a Content-Based Image Retrieval Method

Title
Approximate Query Processing for a Content-Based Image Retrieval Method
Publication Date
2003
Author(s)
Kwan, Paul H
Toraichi, Kazuo
Kitagawa, Hiroyuki
Kameyama, Keisuke
Editor
Editor(s): Vladimir Marik, Werner Retschitzegger, Olga Stepankova
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Springer
Place of publication
Berlin, Germany
Series
Lecture Notes in Computer Science
DOI
10.1007/978-3-540-45227-0_51
UNE publication id
une:6486
Abstract
An approximate query processing approach for a content-based image retrieval method based on probabilistic relaxation labeling is proposed. The novelty lies in the inclusion of a filtering mechanism based on a quasi lower bound on distance in the vector space that effectively spares the matching between the query and a number of database images from going through the expensive step of iterative updating the labeling probabilities. This resembles the two-step filter-and-refine query processing approach that has been applied to k-nearest neighbor (k-NN) retrieval in database research. It is confirmed by experiments that the proposed approach consistently returns a "close approximation" of the accurate result, in the sense of the first k' in the top k output of a k-NN search, while simultaneously reduces the amount of processing required.
Link
Citation
Database and Expert Systems Applications: 14th International Conference, DEXA 2003, Prague, Czech Republic, September 1-5, 2003, Proceedings, p. 517-526
ISBN
3540408061
9783540408062
Start page
517
End page
526

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