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International Afro-European Conference for Industrial Advancement

AECIA 2016: Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016 pp 350–359Cite as

A Novel Arabic Writer Identification System Using Texture Feature on Multi-resolution Levels

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 565))

Abstract

Recognizing an Arabic text with OCR is a complex task caused by the cursive nature of Arabic script. The Arabic letters change forms not only according to their position in the word, but also according to their font in printed text and to their writer in handwritten text. In fact developing a font recognition system or a writer identification system as a pre-recognition step has become a necessity for Arabic text recognition. In this paper, we present an Arabic script recognition system using Curvelet transform for feature extraction in multi-resolution levels. Also, we used a best feature selection algorithm to increase the feature vector size. To validate our proposed system, we tested our system on Arabic handwriting text database ‘KHATT’ using SVM classification. This experiment show a very interesting results.

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Acknowledgements

We acknowledge the financial support of this work by REGIM Laboratory: REsearch Group on Intelligent Machines, University of Sfax, National School of Engineers (ENIS), Sfax, Tunisia.

Author information

Authors and Affiliations

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

    Faten Kallel & Anis Mezghani

  2. MIRACL Laboratory, ISIMS, University of Sfax, Sfax, Tunisia

    Slim Kanoun

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

    Monji Kherallah

Authors
  1. Faten Kallel
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  2. Anis Mezghani
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  3. Slim Kanoun
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  4. Monji Kherallah
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Corresponding author

Correspondence to Monji Kherallah .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Department of Mathematics and Computer, Faculty of Sciences and Techniques, Settat, Morocco

    Abdelkrim Haqiq

  3. Information Technology Department, Faculty of Computers and Information, Giza, Egypt

    Aboul Ella Hassanien

  4. VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

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Kallel, F., Mezghani, A., Kanoun, S., Kherallah, M. (2018). A Novel Arabic Writer Identification System Using Texture Feature on Multi-resolution Levels. In: Abraham, A., Haqiq, A., Ella Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016. AECIA 2016. Advances in Intelligent Systems and Computing, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-319-60834-1_35

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  • DOI: https://doi.org/10.1007/978-3-319-60834-1_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60833-4

  • Online ISBN: 978-3-319-60834-1

  • eBook Packages: EngineeringEngineering (R0)

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