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Aolah Databases for New Arabic Online Handwriting Recognition Algorithm

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Document Analysis and Recognition – ICDAR 2021 Workshops (ICDAR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12916))

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Abstract

Developing an online handwriting recognition system for Arabic script used in pen-based devices plays an important role in making these devices available and usable for Arabic society. This paper is carried out for Arabic script to overcome the difficulties presented in the Arabic language in cursive, overlapping, handwriting variability, different writing styles, delayed strokes, and other challenges. An algorithm for recognizing Arabic strokes written by hand is proposed; since there are some troubles in distinguishing the written stroke for similar characters. The uniqueness of the recommended algorithm is dealing with every stroke in the character separately. Furthermore, in the current research, two novel databases for Arabic characters and Arabic characters’ strokes are generated. The two databases are presented, one for Arabic characters by different writers for the 28 Arabic characters, the other database is extracted from the previous database by taking only the Arabic character strokes. The algorithm used for data collection is distinguished by the ability to deal with each stroke in the written characters separately. The code acts as a simulation of a stylus pen and a touch screen. Stroke capturing is achieved by collecting data points along the path of an input device (stylus pen or mouse) same time those characters are written.

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Acknowledgments

The authors thank all participants’ contribution to (AOLAH) databases formulation. They sincerely appreciated Dr. Omar Abdel-Reheem and Eng. Fatma Gamal, from Aswan faculty of engineering, Aswan University, for their help to facilitate the data collecting process.

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Authors and Affiliations

  1. Faculty of Engineering, Aswan University, Aswan, 81542, Egypt

    Samia Heshmat & Mohamed Abdelnafea

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  1. Samia Heshmat
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  2. Mohamed Abdelnafea
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Corresponding author

Correspondence to Samia Heshmat .

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Editors and Affiliations

  1. Boise State University, Boise, ID, USA

    Elisa H. Barney Smith

  2. Indian Statistical Institute, Kolkata, India

    Umapada Pal

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Heshmat, S., Abdelnafea, M. (2021). Aolah Databases for New Arabic Online Handwriting Recognition Algorithm. In: Barney Smith, E.H., Pal, U. (eds) Document Analysis and Recognition – ICDAR 2021 Workshops. ICDAR 2021. Lecture Notes in Computer Science(), vol 12916. Springer, Cham. https://doi.org/10.1007/978-3-030-86198-8_21

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  • DOI: https://doi.org/10.1007/978-3-030-86198-8_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86197-1

  • Online ISBN: 978-3-030-86198-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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