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Two-stage Content-based Image Retrieval Using the Dimensionality Condensation of Feature Vector  

조정원 (한양대학교 전자통신전파공학과 멀티미디어 연구실)
최병욱 (한양대학교 정보통신대학 정보통신학부)
Abstract
The content-based image retrieval system extracts features of color, shape and texture from raw images, and builds the database with those features in the indexing process. The search in the whole retrieval system is defined as a process which finds images that have large similarity to query image using the feature database. This paper proposes a new two-stage search method in the content-based image retrieval system. The method is that the features are condensed and stored by the property of Cauchy-Schwartz inequality in order to reduce the similarity computation time which takes a mostly response time from entering a query to getting retrieval results. By the extensive computer simulations, we have observed that the proposed two-stage search method successfully reduces the similarity computation time while maintaining the same retrieval relevance as the conventional exhaustive search method. We also have observed that the method is more effective as the number of images and dimensions of the feature space increase.
Keywords
CBIR; two-stage search; dimensionality condensation; fast retrieval.;
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Times Cited By KSCI : 1  (Citation Analysis)
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