Off-line Arabic character recognition: the state of the art

• Published in: Pattern recognition Vol. 31; no. 5; pp. 517 - 530
• Main Author: Amin, Adnan
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.05.1998; Elsevier Science
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Arabic characters; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Feature extraction; Handwriting recognition; Hidden Markov Models; Neural Network classifiers; Off-line recognition; Optical character recognition; Pattern recognition. Digital image processing. Computational geometry; Problem solving, game playing; Segmentation; Theoretical computing; Handwriting recognition; Off-line recognition; Segmentation; Optical character recognition; Neural Network classifiers; Feature extraction; Hidden Markov Models; Arabic characters; Markov chain; Arabic; Classification; Pattern recognition; Neural network; Manuscript character; Learning algorithm; Pattern extraction
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/S0031-3203(97)00084-8

Machine simulation of human reading has been the subject of intensive research for almost three decades. A large number of research papers and reports have already been published on Latin, Chinese and Japanese characters. However, little work has been conducted on the automatic recognition of Arabic characters because of the complexity of printed and handwritten text, and this problem is still an open research field. The main objective of this paper is to present the state of Arabic character recognition research throughout the last two decades.