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Open Vocabulary Recognition of Offline Arabic Handwriting Text Based on Deep Learning

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Intelligent Systems Design and Applications (ISDA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1351))

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Abstract

The offline Arabic text recognition is a substantial problem that has several important applications. It has attracted special emphasis and has become one of the challenging areas of research in the field of computer vision. Deep Neural Networks (DNN) algorithms provide the great performance improvement in problems of sequence recognition such as speech and handwriting recognition. This paper interests on recent Arabic handwriting text recognition researches based on DNN. Our contribution in this work is based on CRNN model with CTC beam search decoder that is used for the first time for handwriting Arabic recognition. The proposed system is an Open-Vocabulary approach that based on character-model recognition.

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Notes

  1. 1.

    http://khatt.ideas2serve.net/.

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Author information

Authors and Affiliations

  1. ISITCom, University of Sousse, 4011, Sousse, Tunisia

    Zouhaira Noubigh

  2. Higher Institute of Industrial Management, University of Sfax, Sfax, Tunisia

    Anis Mezghani

  3. Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia

    Monji Kherallah

Authors
  1. Zouhaira Noubigh
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  2. Anis Mezghani
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  3. Monji Kherallah
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  5. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  6. School of Engineering, Instituto Superior de Engenharia do Porto, Porto, Portugal

    Ana Madureira

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Noubigh, Z., Mezghani, A., Kherallah, M. (2021). Open Vocabulary Recognition of Offline Arabic Handwriting Text Based on Deep Learning. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_9

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