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A Survey on Arabic Handwritten Script Recognition Systems

Soumia Djaghbellou, Abderraouf Bouziane, Abdelouahab Attia, Zahid Akhtar

Source Title: International Journal of Artificial Intelligence and Machine Learning (IJAIML)11(2)

ISSN: 2642-1577|EISSN: 2642-1585|EISBN13: 9781799864110|DOI: 10.4018/IJAIML.20210701.oa9

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MLA

Djaghbellou, Soumia, et al. "A Survey on Arabic Handwritten Script Recognition Systems." IJAIML vol.11, no.2 2021: pp.1-17. http://doi.org/10.4018/IJAIML.20210701.oa9

APA

Djaghbellou, S., Bouziane, A., Attia, A., & Akhtar, Z. (2021). A Survey on Arabic Handwritten Script Recognition Systems. International Journal of Artificial Intelligence and Machine Learning (IJAIML), 11(2), 1-17. http://doi.org/10.4018/IJAIML.20210701.oa9

Chicago

Djaghbellou, Soumia, et al. "A Survey on Arabic Handwritten Script Recognition Systems," International Journal of Artificial Intelligence and Machine Learning (IJAIML) 11, no.2: 1-17. http://doi.org/10.4018/IJAIML.20210701.oa9

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Abstract

The optical character recognition (OCR) system is still an active research field in pattern recognition. Such systems can identify, recognize and distinguish electronically between characters and texts, printed or handwritten. They can also do a transformation of such data type into machine-processable form to facilitate the interaction between user and machine in various applications. In this paper, we present the global structure of an OCR system, with its types (on-line and off-line), categories (printed and handwritten) and its main steps. We also focused on off-line handwritten Arabic character recognition and provided a list of the main datasets publicly available. This paper also presents a survey of the works that have been carried out over recent years. Finally, some open issues and potential research directions have been highlighted