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Proceedings Paper

Image retrieval based on wavelet vector quantization
Author(s): Tao Xia; Jingli Zhou; Shengsheng Yu; Rongfeng Yu
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Paper Abstract

In this paper, we describe a new image indexing and retrieval algorithm for large image databases based on the wavelets decomposition and vector quantization (VQ). The algorithm characterizes the color variations over the spatial extend of the image in a manner that provides semantically-meaningful image comparisons. To speed up retrieval, a two-step procedure is used that first makes a rough comparison based on the coarse features, and then refine the search by performing a fine feature vectors match between the selected images and the query. By adopting these wavelet VQ coding features, images can be compressed and indexed simultaneously, thus decreasing the complexity of database management. For the feasibility and practicality of the approach, a prototype system has been developed and tested with some experiments. Promising results have been obtained in experiments using a database of 15,000 general purposed images.

Paper Details

Date Published: 1 October 1998
PDF: 11 pages
Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); doi: 10.1117/12.323235
Show Author Affiliations
Tao Xia, Huazhong Univ. of Science and Technology (China)
Jingli Zhou, Huazhong Univ. of Science and Technology (China)
Shengsheng Yu, Huazhong Univ. of Science and Technology (China)
Rongfeng Yu, Huazhong Univ. of Science and Technology (United States)


Published in SPIE Proceedings Vol. 3460:
Applications of Digital Image Processing XXI
Andrew G. Tescher, Editor(s)

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