Offline recognition of omnifont Arabic text using the HMM ToolKit (HTK)

被引：46
|
作者：
Khorsheed, M. S. [1 ]
机构：
[1] King Abdulaziz Univ Sci & Technol, Riyadh 11442, Saudi Arabia
来源：
PATTERN RECOGNITION LETTERS | 2007年 / 28卷 / 12期
关键词：
document analysis; pattern analysis and recognition; machine vision; Arabic OCR; HTK;
D O I：
10.1016/j.patrec.2007.03.014
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 presents a cursive Arabic text recognition system. The system decomposes the document image into text line images and extracts a set of simple statistical features from a narrow window which is sliding a long that text line. It then injects the resulting feature vectors to the Hidden Markov Model Toolkit (HTK). HTK is a portable toolkit for speech recognition system. The proposed system is applied to a data corpus which includes Arabic text of more than 600 A4-size sheets typewritten in multiple computer-generated fonts. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码：1563 / 1571
页数：9
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