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Highly Accurate Recognition of Handwritten Arabic Decimal Numbers Based on a Self-Organizing Maps Approach

Amin Alqudah1,2, Hussein R. Al-Zoubi2, Mahmood A. Al-Khassaweneh2,3, Mohammed Al-Qodah1

1 Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
2 Computer Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Jordan.
3 Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA.

* Corresponding Author: Amin Alqudah, email

Intelligent Automation & Soft Computing 2018, 24(3), 493-505.


Handwritten numeral recognition is one of the most popular fields of research in automation because it is used in many applications. Indeed, automation has continually received substantial attention from researchers. Therefore, great efforts have been made to devise accurate recognition methods with high recognition ratios. In this paper, we propose a method for integrating the correlation coefficient with a Self-Organizing Maps (SOM)-based technique to recognize offline handwritten Arabic decimal digits. The simulation results show very high recognition rates compared with the rates achieved by other existing methods.


Cite This Article

A. Alqudah, H. R. Al-Zoubi, M. A. Al-Khassaweneh and M. Al-Qodah, "Highly accurate recognition of handwritten arabic decimal numbers based on a self-organizing maps approach," Intelligent Automation & Soft Computing, vol. 24, no.3, pp. 493–505, 2018.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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