An HMM-based OCR for Persian/Arabic texts

被引:0
|
作者
Ahmadi, A [1 ]
Omatu, S [1 ]
Yoshioka, M [1 ]
机构
[1] Osaka Prefecture Univ, Div Comp & Syst Sci, Dept Engn, Sakai, Osaka 5998531, Japan
关键词
OCR; Persian; Arabic; HMM; character recognition; word recognition;
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
We present a system for recognition of Persian/Arabic texts using hidden Markov model (HMM) in the character level classification. The text is segmented to words at first and from words to characters. A Shadow coding mask are used for extracting the features of characters. Then a Self-Organization Map is employed for clustering the features and reducing the size of inputs. Finally by using the MW classifier and a level building algorithm the words will be composed through recognized characters, The system is evaluated with 10 pages of Persian printed texts and the mean correct classification rate is 95.1% in word level and 99.4% in character level.
引用
收藏
页码:824 / 828
页数:5
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