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Proceedings Paper

Intelligent image database indexing and query system
Author(s): Zijun Yang; C.-C. Jay Kuo
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Paper Abstract

This research investigates the use of image content analysis techniques as a tool of understanding image content, organizing image databases and choosing appropriate low level features as well as semantic meanings for image indexing and retrieval. An intelligent image indexing and query system consisting of semantic classification, composite indexing and interactive query is proposed. In this system, a large collection of images with great varieties is analyzed by the content and categorized into different classes according to distinct characteristics. The semantics of feature descriptors and the relationship between feature descriptors and image contents are then explored. Finally, a composite indexing and interactive retrieval procedure using best low-level features and high-level understanding is developed to achieve a robust image query performance.

Paper Details

Date Published: 18 October 1999
PDF: 12 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365860
Show Author Affiliations
Zijun Yang, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 3808:
Applications of Digital Image Processing XXII
Andrew G. Tescher, Editor(s)

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