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

This paper presents a graph-based framework for the segmentation of Arabic tent. The same framework is used to extract font independent structural features from the text that tire 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 (LAG) representation ut 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 clots and diacritic signs. The final character recognition is achieved by using a regular grammar that describes how characters are composed from scripts.