Handwritten character recognition by Fourier descriptors and neural network

被引：0
|
作者：
Chung, YY [1 ]
Wong, MT [1 ]
机构：
[1] Queensland Univ Technol, Sch Elect Elect & Syst Engn, Space Ctr Satellite Navigat, Brisbane, Qld 4001, Australia
来源：
IEEE TENCON'97 - IEEE REGIONAL 10 ANNUAL CONFERENCE, PROCEEDINGS, VOLS 1 AND 2: SPEECH AND IMAGE TECHNOLOGIES FOR COMPUTING AND TELECOMMUNICATIONS | 1997年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes a handwritten character recognition system by using a multi-layer perceptron with one hidden layer. Features extracted from the handwritten characters are Fourier Descriptor (FD) and Border Transition Technique (BTT) [I]. The FD's and Border transition values are input to the neural network which is then trained by backpropagation. Test results indicate that FD combined with BTT can provide good recognition accuracy (96%) for handwritten numerals 0 to 9.
引用
收藏
页码：391 / 394
页数：4
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