
Proceedings Paper
Image object recognition based on the Zernike moment and neural networksFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper first give a comprehensive discussion about the concept of artificial neural network its research methods and the relations with information processing. On the basis of such a discussion, we expound the mathematical similarity of artificial neural network and information processing. Then, the paper presents a new method of image recognition based on invariant features and neural network by using image Zernike transform. The method not only has the invariant properties for rotation, shift and scale of image object, but also has good fault tolerance and robustness. Meanwhile, it is also compared with statistical classifier and invariant moments recognition method.
Paper Details
Date Published: 25 March 1998
PDF: 5 pages
Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); doi: 10.1117/12.304843
Published in SPIE Proceedings Vol. 3390:
Applications and Science of Computational Intelligence
Steven K. Rogers; David B. Fogel; James C. Bezdek; Bruno Bosacchi, Editor(s)
PDF: 5 pages
Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); doi: 10.1117/12.304843
Show Author Affiliations
Jianwei Wan, National Univ. of Defense Technology (China)
Ling Wang, National Univ. of Defense Technology (China)
Ling Wang, National Univ. of Defense Technology (China)
Fukan Huang, National Univ. of Defense Technology (China)
Liangzhu Zhou, National Univ. of Defense Technology (China)
Liangzhu Zhou, National Univ. of Defense Technology (China)
Published in SPIE Proceedings Vol. 3390:
Applications and Science of Computational Intelligence
Steven K. Rogers; David B. Fogel; James C. Bezdek; Bruno Bosacchi, Editor(s)
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