
Proceedings Paper
Hierarchical clustering algorithm for fast image retrievalFormat | Member Price | Non-Member Price |
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Paper Abstract
Image retrieval systems, which compare the query image exhaustively with each individual image in the database, are not scalable to large databases. A scalable search system should ensure that the search time does not increase linearly with the number of images in the database. We present a clustering based indexing technique, where the images in the database are grouped into clusters of images, with similar color content using a hierarchical clustering algorithm. At search time, the query image is not compared with all the images in the database, but only with a small subset. Experiments show that this clustering-based approach offers a superior response time with high retrieval accuracy. Experiments with different database sizes indicate that for a given retrieval accuracy, the search time does not increase linearly with the database size.
Paper Details
Date Published: 17 December 1998
PDF: 9 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333862
Published in SPIE Proceedings Vol. 3656:
Storage and Retrieval for Image and Video Databases VII
Minerva M. Yeung; Boon-Lock Yeo; Charles A. Bouman, Editor(s)
PDF: 9 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333862
Show Author Affiliations
Santhana Krishnamachari, Philips Research (United States)
Mohamed Abdel-Mottaleb, Philips Research (United States)
Published in SPIE Proceedings Vol. 3656:
Storage and Retrieval for Image and Video Databases VII
Minerva M. Yeung; Boon-Lock Yeo; Charles A. Bouman, Editor(s)
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