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Proceedings Paper

Optimization of wavelet filters to improve recognition accuracy of a volume holographic correlator
Author(s): Wenyi Feng; Yingbai Yan; Gaogui Huang; Guofan Jin; Minxian Wu
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Paper Abstract

The concept of the associative storage in a photorefractive material offers suitable methods to design a multichannel correlator for image identification. Wavelet transform is introduced to improve recognition accuracy of the system, which provides a sharper peak and lower sidelobes than the conventional correlation. The recognition accuracy of the system is significantly affected by the choice of wavelet function and its parameters. A neural network is proposed to optimize parameters of the wavelet filters to improve recognition performance of the system. The object function for optimization is to maximize the difference of correlation outputs among different categories and minimize the variation of correlation outputs in a same category. Simulation and experimental results are given to testify the effect of optimization. Its application in human face recognition is studied. The results show that it is attractive to use neural network to refine parameters of filters.

Paper Details

Date Published: 26 October 1999
PDF: 8 pages
Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); doi: 10.1117/12.366768
Show Author Affiliations
Wenyi Feng, Tsinghua Univ. (United States)
Yingbai Yan, Tsinghua Univ. (China)
Gaogui Huang, Tsinghua Univ. (China)
Guofan Jin, Tsinghua Univ. (China)
Minxian Wu, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 3813:
Wavelet Applications in Signal and Image Processing VII
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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