Optical character recognition of arabic printed text

S. Taha, Y. Babiker, M. Abbas
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引用次数: 13

Abstract

Optical character recognition (OCR) systems improve human- machine interaction. They are widely used in many areas such as editing and storing previously printed or handwritten documents. Much of research has been done regarding the identification of Latin, Japanese and Chinese characters. However, very little investigation has been performed regarding Arabic recognition. Probably the reason is limitation of IT activities in Arabic speaking countries and the difficulty and complexity of Arabic characters identification compared to the others. More difficulties are introduced from the cursive nature of Arabic text. In this paper, a technique has been employed to segment printed Arabic text in order to separate the Arabic characters and then extracting powerful features for each to be recognized. In-order to recognize characters, those features are then compared with a pre-prepared database fields. Although the database was prepared from characters written in Time New Roman font, experimental results show the relatively high accuracy of the method developed when it is tested on several sizes of several fonts beside Time New Roman font.
阿拉伯语印刷文本的光学字符识别
光学字符识别(OCR)系统改善了人机交互。它们被广泛应用于许多领域,如编辑和存储以前打印或手写的文件。关于拉丁文、日文和汉字的识别,已经做了大量的研究。但是,很少对阿拉伯语的承认进行调查。原因可能是阿拉伯语国家IT活动的限制,以及与其他国家相比,阿拉伯字符识别的难度和复杂性。更多的困难是介绍了从草书的阿拉伯文本的性质。本文采用一种对印刷阿拉伯文文本进行分割的技术,将阿拉伯文字符分离出来,然后为每个字符提取强大的特征进行识别。为了识别字符,然后将这些特征与预先准备好的数据库字段进行比较。虽然数据库是由时代新罗马字体编写的,但实验结果表明,在时代新罗马字体之外的几种字体的几种大小上进行测试时,所开发的方法具有较高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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