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Optical Engineering

Optical pattern recognition by extracting least substructuring elements
Author(s): Yue Liu; Shu Chen; Pengyi Guo; Jinyuan Shen; Hongchen Zhai; YanXin Zhang
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Paper Abstract

Optical pattern recognition and classification are commonly implemented by means of correlation, and a specialized filter for the patterns to be recognized must be constructed first. Although it has the inherent advantages of high speed, shift invariance, and high distin- guishability, how to build an effective and easily implemented filter or group of filters still remains an open problem. By combining the methods of correlation filtering, transform encoding, and neural network mapping, a least substructuring elements (LSE) extracting method is proposed in this paper. Some basic substructuring elements of a specific group of patterns to be processed could be extracted to compose masks in the least number. Computer simulation upon the 26 English capital letters is provided. One integrated hybrid optoelectronic implementation system is described.

Paper Details

Date Published: 1 October 1999
PDF: 5 pages
Opt. Eng. 38(10) doi: 10.1117/1.602221
Published in: Optical Engineering Volume 38, Issue 10
Show Author Affiliations
Yue Liu, Nankai Univ. (China)
Shu Chen, Nankai Univ. (China)
Pengyi Guo, Nankai Univ. (China)
Jinyuan Shen, Nankai Univ. (China)
Hongchen Zhai, Nankai Univ. (China)
YanXin Zhang, Nankai Univ. (China)


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