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

机译:基于图的分割和特征提取框架,用于阿拉伯文字识别

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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.
机译:本文提出了一种基于图的阿拉伯文本分割框架。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。本文的主要贡献是一种新的基于图的结构分割方法,该方法基于基线和文本的线邻接图表示之间的拓扑关系。文本被细分为我们称为“脚本”的子字符单元。结构分析方法用于识别这些单元。使用不同的分类器来识别点和变音符号。最终的字符识别是通过使用常规语法来实现的,该语法描述了脚本是如何组成字符的。

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