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A Time Delay Neural Network for Online Arabic Handwriting Recognition

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

Handwriting recognition is an interesting part in pattern recognition field. In the last decade, several approaches are focused on online handwriting recognition because the very rapid growth of new technologies in the field of data entry. In this paper, we propose a new system for online Arabic handwriting recognition based on beta-elliptic model which allow to segment the trajectory into segments called strokes by inspecting the extremums points of velocity profile and extract their dynamic and geometric profiles. These strokes are used to train the Time Delay Neural Network (TDNN) which is able to represent the sequential aspect of input data. To evaluate our method, we have used a total of 25000 Arabic letters from the LMCA database. Our experimental results demonstrate the effectiveness of our proposed method and show recognition rates exceeds the 95%.

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Authors and Affiliations

  1. National School of Engineers of Sfax (ENIS), University of Sfax, Sfax, Tunisia

    Ramzi Zouari & Houcine Boubaker

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

    Monji Kherallah

Authors
  1. Ramzi Zouari
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  2. Houcine Boubaker
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  3. Monji Kherallah
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Corresponding author

Correspondence to Ramzi Zouari .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Zouari, R., Boubaker, H., Kherallah, M. (2017). A Time Delay Neural Network for Online Arabic Handwriting Recognition. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_99

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_99

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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