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Isolated Handwritten Arabic Character Recognition Using Convolutional Neural Networks: An Overview

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Innovations in Smart Cities Applications Volume 7 (SCA 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 938))

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Abstract

Arabic Handwriting Recognition (AHR) is a research area of great importance, given the intricacies of Arabic script. The recognition of Isolated Handwritten Arabic Characters (IHAC) is a crucial phase in AHR, and significant progress has been made in recent years, primarily due to the adoption of Convolutional Neural Networks (CNN). CNN has emerged as a powerful learning technique, dominating various computer vision-related research domains. Notably, CNNs have been extensively utilized for IHAC recognition since 2017. This paper presents an analysis of CNN-based methods employed in IHAC recognition. We delve into the advancements made in network architectures, training strategies, datasets, and results. The findings from this review emphasize the immense potential of CNN-based methods in IHAC recognition and shed light on future research directions to tackle the challenges associated with this field. Overall, CNN-based methods hold promising prospects for improving the accuracy and efficiency of IHAC recognition, which can have far-reaching applications in document analysis, text recognition, and language processing.

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Authors and Affiliations

  1. Ibn Tofail University, Kenitra, Morocco

    Mohsine El Khayati, Ismail Kich & Youssfi Elkettani

Authors
  1. Mohsine El Khayati
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  2. Ismail Kich
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  3. Youssfi Elkettani
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Corresponding author

Correspondence to Mohsine El Khayati .

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Editors and Affiliations

  1. Faculty of Sciences and Techniques, Abdelmalek Essaadi University, Tangier, Morocco

    Mohamed Ben Ahmed

  2. Fac Sciences et Techniques de Tanger, Université Abdelmalek Essaâdi, Tangier, Morocco

    Anouar Abdelhakim Boudhir

  3. École Spéciale des Travaux Publics, Paris, France

    Rani El Meouche

  4. Computer Engineering Department, Karabük University, Karabük, Türkiye

    İsmail Rakıp Karaș

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El Khayati, M., Kich, I., Elkettani, Y. (2024). Isolated Handwritten Arabic Character Recognition Using Convolutional Neural Networks: An Overview. In: Ben Ahmed, M., Boudhir, A.A., El Meouche, R., Karaș, İ.R. (eds) Innovations in Smart Cities Applications Volume 7. SCA 2023. Lecture Notes in Networks and Systems, vol 938. Springer, Cham. https://doi.org/10.1007/978-3-031-54376-0_12

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  • DOI: https://doi.org/10.1007/978-3-031-54376-0_12

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  • Print ISBN: 978-3-031-54375-3

  • Online ISBN: 978-3-031-54376-0

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