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Approximate Query Processing for a Content-Based Image Retrieval Method |
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Editor(s): Vladimir Marik, Werner Retschitzegger, Olga Stepankova |
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Lecture Notes in Computer Science |
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10.1007/978-3-540-45227-0_51 |
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| Abstract |
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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. |
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Database and Expert Systems Applications: 14th International Conference, DEXA 2003, Prague, Czech Republic, September 1-5, 2003, Proceedings, p. 517-526 |
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