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

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.

[1]  Robert M. Haralick,et al.  Segmentation-free word recognition with application to Arabic , 1995, Proceedings of 3rd International Conference on Document Analysis and Recognition.

[2]  Talaat S. El-Sheikh,et al.  Computer recognition of arabic cursive scripts , 1988, Pattern Recognit..

[3]  Theodosios Pavlidis,et al.  On the Recognition of Printed Characters of Any Font and Size , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Hussein Almuallim,et al.  A Method of Recognition of Arabic Cursive Handwriting , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Noureddine Ellouze,et al.  A robust approach for Arabic printed character segmentation , 1995, ICDAR.

[6]  Richard M. Schwartz,et al.  An Omnifont Open-Vocabulary OCR System for English and Arabic , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Adnan Amin,et al.  Off-line Arabic character recognition: the state of the art , 1998, Pattern Recognit..

[8]  Y. Lecourtier,et al.  A new approach for Latin/Arabic character segmentation , 1995, Proceedings of 3rd International Conference on Document Analysis and Recognition.

[9]  David G. Stork,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[10]  S. S. Upda,et al.  Recognition of Arabic Characters , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  T.C.R.S. Fowler.  A reading machine for the blind , 1983 .

[12]  Theo Pavlidis,et al.  A vectorizer and feature extractor for document recognition , 1986 .

[13]  Adnan Amin,et al.  Machine recognition and correction of printed Arabic text , 1989, IEEE Trans. Syst. Man Cybern..

[14]  Sherif Sami El-Dabi,et al.  Arabic character recognition system: A statistical approach for recognizing cursive typewritten text , 1990, Pattern Recognit..