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Proceedings Paper

Differential compression and optimal caching methods for content-based image search systems
Author(s): Di Zhong; Shih-Fu Chang; John R. Smith
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Paper Abstract

Compression and caching are two important issues for a large on-line image server. In this paper, we propose a new approach to compression by exploring similarity in large image archives. An adaptive vector quantization approach using content categorizations, including both the semantic level and the feature level, is developed to provide a differential compression scheme. We show that this scheme is able to support flexible and optimal caching strategies. The experimental results demonstrate that the proposed technique can improve the compression rate by about 20 percent compared to JPEG compression, and can improve the retrieval response by 5 percent to 20 percent under different typical access scenarios.

Paper Details

Date Published: 24 August 1999
PDF: 10 pages
Proc. SPIE 3846, Multimedia Storage and Archiving Systems IV, (24 August 1999); doi: 10.1117/12.360445
Show Author Affiliations
Di Zhong, Columbia Univ. (United States)
Shih-Fu Chang, Columbia Univ. (United States)
John R. Smith, IBM Thomas J. Watson Research Ctr. (United States)

Published in SPIE Proceedings Vol. 3846:
Multimedia Storage and Archiving Systems IV
Sethuraman Panchanathan; Shih-Fu Chang; C.-C. Jay Kuo, Editor(s)

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