Pattern identification with an improved synthetic discrimination function

Zikuan Chen; Guoguang Mu

doi:10.1117/12.177525

1 September 1994 Pattern identification with an improved synthetic discrimination function

Zikuan Chen, Guoguang Mu

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Optical Engineering, Vol. 33, Issue 9, (September 1994). https://doi.org/10.1117/12.177525

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.

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Zikuan Chen and Guoguang Mu "Pattern identification with an improved synthetic discrimination function," Optical Engineering 33(9), (1 September 1994). https://doi.org/10.1117/12.177525

Published: 1 September 1994

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KEYWORDS

Fingerprint recognition

Binary data

Distortion

Image classification

Optical engineering

Optical filters

Pattern recognition

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