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Arabic Handwritten Recognition Using Deep Learning: A Survey

Arabian Journal for Science and Engineering volume 47, pages 9943–9963 (2022)Cite this article

Abstract

In recent times, many research projects and experiments target machines that automatically recognize handwritten characters, but most of them are done in Latin. Recognizing handwritten Arabic characters is a complicated process compared to English and other languages as a nature of Arabic words. In the past few years, deep learning approaches have been increasingly used in the field of Arabic recognition. This paper aims to categorize, analyze and presents a comprehensive survey in Arabic handwritten recognition literature, focusing on state-of-the-art methods for deep learning in feature extraction. The paper focuses on offline text recognition, with a detailed discussion of the systematic analysis of the literature. Additionally, the paper is critically analyzing the current literature and identifying the problem areas and challenges faced by the previous studies. After investigating the studies, a new classification of the literature is proposed. Besides, an analysis is performed based on the findings, and several issues and challenges related to the recognition of Arabic scripts are discussed.

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Authors and Affiliations

  1. Department of Computer Engineering, College of Engineering and Computer Science, Mustaqbal University, Buraydah, Qassim, Saudi Arabia

    Naseem Alrobah

  2. Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia

    Saleh Albahli

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  1. Naseem Alrobah
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  2. Saleh Albahli
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Correspondence to Saleh Albahli.

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Alrobah, N., Albahli, S. Arabic Handwritten Recognition Using Deep Learning: A Survey. Arab J Sci Eng 47, 9943–9963 (2022). https://doi.org/10.1007/s13369-021-06363-3

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