DocumentCode :
296002
Title :
Writer verification using multiple neural networks
Author :
Yan, Hong ; Wu, Jing
Author_Institution :
Dept. of Electr. Eng., Sydney Univ., NSW, Australia
Volume :
1
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
414
Abstract :
A writer identification system is described an this paper based on the use of multiple neural networks. In this system a set of Chinese characters are written by the people who are registered in the computer. One neural network is trained for all samples of each character. In the testing mode, a person is asked to write the same set of characters and the decisions of all neural network are combined to identify the person. The method has been verified to work highly reliably on real testing data and it compares favorably with the distance based method proposed by other researchers
Keywords :
biometrics (access control); eigenvalues and eigenfunctions; feedforward neural nets; handwriting recognition; image matching; Chinese character recognition; biometrics; eigenvalues; eigenvectors; handwriting matching; multiple neural networks; writer identification system; Computer network reliability; Databases; Eigenvalues and eigenfunctions; Humans; Law; Legal factors; Multi-layer neural network; Neural networks; Shape measurement; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.488136
Filename :
488136
Link To Document :
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