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Optical Engineering

Pattern identification with an improved synthetic discrimination function
Author(s): Zikuan Chen; Guoguang Mu
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Paper Abstract

An improved synthetic discriminant function for pattern identification is proposed, which is suitable for discriminating one class from all other classes with distortion invariance. By training the samples and their complementary versions from a specified class simultaneously, the distances between the trained class and all other classes are increased in detection space, and therefore high discrimination results. An application to fingerprint identification is given.

Paper Details

Date Published: 1 September 1994
PDF: 3 pages
Opt. Eng. 33(9) doi: 10.1117/12.177525
Published in: Optical Engineering Volume 33, Issue 9
Show Author Affiliations
Zikuan Chen, Nankai Univ. (China)
Guoguang Mu, Nankai Univ. (China)

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