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Title: Approximate Query Processing for a Content-Based Image Retrieval Method
Contributor(s): Kwan, Paul H  (author); Toraichi, Kazuo (author); Kitagawa, Hiroyuki (author); Kameyama, Keisuke (author)
Publication Date: 2003
DOI: 10.1007/978-3-540-45227-0_51
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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.
Publication Type: Conference Publication
Conference Details: DEXA 2003: 14th International Conference on Database and Expert Systems Applications, Prague, Czech Republic, 1st - 5th September, 2003
Source of Publication: Database and Expert Systems Applications: Proceedings of the 14th International Conference, DEXA 2003, p. 517-526
Publisher: Springer-Verlag
Place of Publication: Berlin, Germany
Field of Research (FOR): 080108 Neural, Evolutionary and Fuzzy Computation
080109 Pattern Recognition and Data Mining
080106 Image Processing
Socio-Economic Objective (SEO): 890202 Application Tools and System Utilities
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
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Series Name: Lecture Notes in Computer Science
Series Number : 2736
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