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

来源：

KNOWLEDGE-BASED INTELLIGENT INFORMATION ENGINEERING SYSTEMS & ALLIED TECHNOLOGIES, PTS 1 AND 2 | 2001年 / 69卷

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

页码：824 / 828

页数：5

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