A graph-based segmentation and feature extraction framework for Arabic text recognition

A. Elgammal, M. Ismail
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引用次数: 47

Abstract

This paper presents a graph-based framework for the segmentation of Arabic text. The same framework is used to extract font independent structural features from the text that are used in the recognition. The major contribution of this paper is a new graph-based structural segmentation approach based on the topological relation between the baseline and the line adjacency graph representation of the text. The text is segmented to sub-character units that we call "scripts". A structure analysis approach is used for recognition of these units. A different classifier is used to recognize dots and diacritic signs. The final character recognition is achieved by using a regular grammar that describes how characters are composed from scripts.
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基于图的阿拉伯语文本识别分割和特征提取框架
提出了一种基于图的阿拉伯语文本分词框架。使用相同的框架从识别中使用的文本中提取与字体无关的结构特征。本文的主要贡献是基于文本的基线和线邻接图表示之间的拓扑关系,提出了一种新的基于图的结构分割方法。文本被分割成子字符单元,我们称之为“脚本”。采用结构分析方法对这些单元进行识别。使用不同的分类器来识别点和变音符号。最后的字符识别是通过使用描述如何从脚本组成字符的规则语法来实现的。
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