ONLINE ARABIC/PERSIAN CHARACTER RECOGNITION USING NEURAL NETWORK CLASSIFIER AND DCT FEATURES

被引：0
|
作者：
Khodadad, Iman [1 ]
Sid-Ahmed, Maher [1 ]
Abdel-Raheem, Esam [1 ]
机构：
[1] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada
来源：
2011 IEEE 54TH INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS) | 2011年
关键词：
Pattern recognition; DCT; Neural networks;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Online handwriting recognition is gaining interest due to the increase of pen computing applications and availability of tablet devices. The recognition of Arabic/Persian (A/P) characters is different from western handwriting, in which different calligraphic styles and cursive nature makes automatic recognition a more challenging and complicated task. In this paper, a new method is proposed to represent A/P characters. The proposed method incorporates a new set feature vectors suitable for A/P character set. A recognition system utilizing these set of features is developed for handwritten A/P characters. The result of the overall recognition system compare favorably with previous techniques.
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页数：4
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