Survey of Offline Arabic Handwriting Word Recognition

  • Haitham Qutaiba GhadhbanEmail author
  • Muhaini Othman
  • Noor Azah Samsudin
  • Mohd Norasri Bin Ismail
  • Mustafa Raad Hammoodi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 978)


The field of Arabic handwriting recognition and translation is currently experiencing rapid growth in terms of research, which is evident in the coverage of major conferences and journals that specialise in the area of handwriting recognition. Against this backdrop, a significant increase has been observed in the classification and features techniques used, as compared to some years back. Researchers have put in more efforts geared towards building a variety of databases for Arabic handwriting recognition. This article aims to provide a comprehensive survey of advances in Arabic offline handwriting recognition. We have been provided details of availability Arabic databases with limitation. Further, we focus on techniques of feature extraction and different variety of classification approaches such as ANN, HMM, SVM that used in Arabic handwriting recognition.


Offline handwriting recognition Arabic datasets Feature extraction Classifiers 



The author would like to acknowledge Universiti Tun Hussein Onn Malaysia (UTHM) for the support of this research under the Tier 1 Grant: vot H093.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Haitham Qutaiba Ghadhban
    • 1
    Email author
  • Muhaini Othman
    • 1
  • Noor Azah Samsudin
    • 1
  • Mohd Norasri Bin Ismail
    • 1
  • Mustafa Raad Hammoodi
    • 1
  1. 1.Software Engineering DepartmentUniversiti Tun Hussein Onn MalaysiaParit Raja, Batu PahatMalaysia

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