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Optical Engineering

Off-line writer verification utilizing multiple neural networks
Author(s): Kai Huang; Jing Wu; Hong Yan
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Paper Abstract

A writer verification system based on multiple neural network classifiers is described, aimed to be easily extendable. Each writer registers with the system by writing a set of discrete Chinese characters. One neural network is constructed for each enrolled character class on a per-person or a per-subgroup basis. The decisions from individual network classifiers are combined by voting. The method has been verified to work reliably on our testing database: a verification rate above 96% is achieved on short-term data.

Paper Details

Date Published: 1 November 1997
PDF: 7 pages
Opt. Eng. 36(11) doi: 10.1117/1.601550
Published in: Optical Engineering Volume 36, Issue 11
Show Author Affiliations
Kai Huang, Univ. of Sydney (Australia)
Jing Wu, Motorola Australian Research Ctr (Australia)
Hong Yan, Univ. of Sydney (Hong Kong)


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