A Novel Arabic Words Recognition System Using Hyperplane Classifier

Authors

  • Dr.Mahmoud Abdegadir Khalifa College of Computing and Information Technology University of Bisha, Bisha, Saudi Arabia
  • Dr.Ammar Mohammed Ali Chemical Engineering Department, University of Technology, Iraq
  • Dr.Saif Ali Abd Alradha Alsaidi College of Education For Pure Science , Wasit University, Iraq
  • Dr.liying Zheng Harbin Engineering University, China
  • Dr.Nahla Fadel Alwan Chemical Engineering Department, University of Technology, Iraq
  • Dr.Gadiaa Saeed Mahdi Chemical Engineering Department, University of Technology, Iraq

DOI:

https://doi.org/10.31185/wjcm.Vol1.Iss2.45

Abstract

Topic of exhaustive study for about past decades has been carried out in machine imitation of human reading. a small number of investigates have been accepted on the detection of cursive font writing like Arabic texts for its individual challenge and difficulty .In this work, a novel technique for automatic Arabic font recognition is proposed to demonstrate an suitable recognition rate for multi fonts styles and multi sizes of Arabic word images.

The scheme can be classified into a number of steps. First, segmenting Arabic line into words depending on the vertical projection and dynamic threshold then we implicated  each  Arabic word as a class by ignoring segmenting the word into characters .Second ,normalizing step, the size of Arabic word images varies from each other .The system converts  the images that contribution into a new size that  is divisible by "N" without remainder, to decrease the difficulty of feature extraction and recognition of  the system that may allow images from different resources, Third,  feature extraction step which is based on apply the ratio of vertical sliding strips as a features. Finally, multi class support vector machine (one versus one technique)is used as a classifier .This method was estimated on off line printed fonts, five Arabic fonts, (Andalus, Arial, Simplified Arabic, Tahoma and Traditional Arabic) were used and the average  recognition rate of all fonts was 95.744%.

Author Biographies

  • Dr.liying Zheng, Harbin Engineering University, China

     

     

  • Dr.Nahla Fadel Alwan, Chemical Engineering Department, University of Technology, Iraq

     

     

  • Dr.Gadiaa Saeed Mahdi, Chemical Engineering Department, University of Technology, Iraq

     

     

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Published

2022-06-30

Issue

Vol. 1 No. 2 (2022)

Section

Computer

License

Copyright (c) 2022 Dr.Mahmoud Abdegadir Khalifa, Dr.Ammar Mohammed Ali, Dr.Saif Ali Abd Alradha Alsaidi, Dr.liying Zheng, Dr.Nahla Fadel Alwan, Dr.Gadiaa Saeed Mahdi

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. Abdegadir Khalifa, A. Mohammed Ali, Dr.Saif Ali Abd Alradha Alsaidi, liying Zheng, N. Fadel Alwan, and G. Saeed Mahdi, “A Novel Arabic Words Recognition System Using Hyperplane Classifier”, WJCMS, vol. 1, no. 2, pp. 8–13, Jun. 2022, doi: 10.31185/wjcm.Vol1.Iss2.45.