HMM-based system for recognizing words in historical Arabic manuscript

被引：7
|
作者：
Khorsheed, M. S. [1 ]
机构：
[1] King Abdulaziz City Sci & Technol, Comp & Elect Res Inst, Riyadh 11442, Saudi Arabia
来源：
INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION | 2007年 / 22卷 / 04期
关键词：
Arabic character recognition; HMMs; cursive text; off-line; Fourier transform;
D O I：
10.2316/Journal.206.2007.4.206-3000
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an omni-font Arabic word recognition system. The system is based on multiple Hidden Markov Models (HMMs). Each word in the lexicon is represented with a distinct HMM. The proposed system first extracts a set of spectral features from word images, then uses those features to tune HMM parameters. The performance of the proposed system is assessed using a corpus that includes both handwritten and computer-generated scripts. The likelihood probability of the input pattern is calculated against each word model and the pattern is assigned to the model with the highest probability.
引用
收藏
页码：294 / 303
页数：10
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