Off-line writer verification utilizing multiple neural networks

被引：5
|
作者：
Huang, K [2 ]
Wu, J
Yan, H
机构：
[1] MOTOROLA AUSTRALIAN RES CTR,BOTANY,NSW 2019,AUSTRALIA
[2] UNIV SYDNEY,DEPT ELECT ENGN,SYDNEY,NSW 2006,AUSTRALIA
来源：
OPTICAL ENGINEERING | 1997年 / 36卷 / 11期
关键词：
writer verification; off-line information; classifier combination;
D O I：
10.1117/1.601550
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
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. (C) 1997 Society of Photo-Optical Instrumentation Engineers.
引用
收藏
页码：3127 / 3133
页数：7
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