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Proceedings Paper

An object recognition method based on fuzzy theory and BP networks
Author(s): Chuan Wu; Ming Zhu; Dong Yang
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Paper Abstract

It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling, shifting, rotation if eigenvectors can not be chosen appropriately. In order to solve this problem, the image is edged, the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively, correctly and quickly.

Paper Details

Date Published: 20 January 2006
PDF: 8 pages
Proc. SPIE 6027, ICO20: Optical Information Processing, 602738 (20 January 2006); doi: 10.1117/12.668321
Show Author Affiliations
Chuan Wu, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Ming Zhu, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Dong Yang, Changchun Univ. of Technology (China)


Published in SPIE Proceedings Vol. 6027:
ICO20: Optical Information Processing
Yunlong Sheng; Songlin Zhuang; Yimo Zhang, Editor(s)

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