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Arabic Handwriting Word Recognition Based on Convolutional Recurrent Neural Network

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WITS 2020

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 745))

Abstract

The success of any words-characters recognition system depends on board parameters such as the language (Arabic, Latin, Indi …), the document type (writing or typing), based or free-segmentation, pretreatment, features extraction and classification approaches. Within these fields, Building a robust and viable recognition system for Arabic handwritten has always been a challenging task since a long time. In this study, we propose an end-to-end system based on deep Convolutional Recurrent Neural Network CNN/RNN; we trained our system on IFN/ENIT extended database in order to improve our results.

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Authors and Affiliations

  1. Laboratory of Information and Interdisciplinary Physics, ENS, University Sidi Mohamed Ben Abdellah, Fes, Morocco

    Manal Boualam, Youssef Elfakir, Ghizlane Khaissidi & Mostafa Mrabti

Authors
  1. Manal Boualam
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  2. Youssef Elfakir
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  3. Ghizlane Khaissidi
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  4. Mostafa Mrabti
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Corresponding author

Correspondence to Manal Boualam .

Editor information

Editors and Affiliations

  1. Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Saad Bennani

  2. Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Younes Lakhrissi

  3. Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Ghizlane Khaissidi

  4. Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Anass Mansouri

  5. Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Youness Khamlichi

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Cite this paper

Boualam, M., Elfakir, Y., Khaissidi, G., Mrabti, M. (2022). Arabic Handwriting Word Recognition Based on Convolutional Recurrent Neural Network. In: Bennani, S., Lakhrissi, Y., Khaissidi, G., Mansouri, A., Khamlichi, Y. (eds) WITS 2020. Lecture Notes in Electrical Engineering, vol 745. Springer, Singapore. https://doi.org/10.1007/978-981-33-6893-4_79

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  • DOI: https://doi.org/10.1007/978-981-33-6893-4_79

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-6892-7

  • Online ISBN: 978-981-33-6893-4

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