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Proceedings Paper

A feedforward control idea for CBIR using obvious features
Author(s): Xingfeng Chen; Xingfa Gu; Jiping Chen; Tao Yu; Yun Liu
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Paper Abstract

CBIR (Content-Based Image Retrieval), which includes feature selection, feature extraction, similarity measurement and user feedback parts, often uses feedback to improve the retrieval accuracy. But there are two problems of Feedback: 1) improving the retrieval accuracy, but also increasing the user's operation complexity; 2) it is not easy to confirm the weight values of each feature in similarity measurement. In this paper, a feedforward idea from Control Theory was used in CBIR system. The method is to select an obvious feature automatically from multi-features, and then give a higher weight value to the obvious feature in the similarity measurement. Experiment results show that the method presented is efficient in image retrieval based on feedforward idea.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74954Q (30 October 2009); doi: 10.1117/12.833043
Show Author Affiliations
Xingfeng Chen, Institute of Remote Sensing Applications (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
National Space Administration (China)
Xingfa Gu, Institute of Remote Sensing Applications (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
National Space Administration (China)
Jiping Chen, Institute of Remote Sensing Applications (China)
National Space Administration (China)
Tao Yu, Institute of Remote Sensing Applications (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
National Space Administration (China)
Yun Liu, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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