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Proceedings Paper

The research with Gabor wavelet neural networks algorithm on target recognition
Author(s): Hongguang Sun; Yuxue Pan; Jingbo Zhang
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Paper Abstract

The Paper is the study of Gabor wavelet neural network algorithm and its application in gray image target recognition. The mostly thought t are real time recognizing gray image target with Gabor wavelet neural networks algorithm. The main thoughts are through combing the forward neural networks (BP net) with Gabor wavelet based on they were applied in target feature extraction and recognition. A model of Gabor wavelet neural network is constructed with automatic target recognition, the good impact is gained when it is applied target recognition. The principle of Gabor filter is expounded. The multi-channel Gabor filter is designed based on theory and practicality, the neural network recognizing algorithm based on multi-channel Gabor filter feature is presented. Training algorithm of Gabor wavelet neural networks model was given out. Principally analyzed Gabor wavelet neural networks from theory, in the mean time training algorithm of Gabor wavelet network suited to target recognition was designed by BP algorithm. Theory and simulate experiment indicated the astringency and robustness of this algorithm excelled BP net. Target was recognized by this algorithm not only increased recognition precision but also overcame the bug of BP algorithm get in minimum

Paper Details

Date Published: 8 February 2005
PDF: 8 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.572592
Show Author Affiliations
Hongguang Sun, Changchun Univ. of Science and Technology (China)
Northeast Normal Univ. (China)
Yuxue Pan, Changchun Univ. of Science and Technology (China)
Jingbo Zhang, Northeast Normal Univ. (China)


Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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