Open Access
ARTICLE
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,
Intelligent Automation & Soft Computing 2018, 24(3), 493-505. https://doi.org/10.31209/2018.100000005
Abstract
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.
Keywords
Cite This Article
APA Style
Alqudah, A., Al-Zoubi, H.R., Al-Khassaweneh, M.A., Al-Qodah, M. (2018). Highly accurate recognition of handwritten arabic decimal numbers based on a self-organizing maps approach. Intelligent Automation & Soft Computing, 24(3), 493-505. https://doi.org/10.31209/2018.100000005
Vancouver Style
Alqudah A, Al-Zoubi HR, Al-Khassaweneh MA, Al-Qodah M. Highly accurate recognition of handwritten arabic decimal numbers based on a self-organizing maps approach. Intell Automat Soft Comput . 2018;24(3):493-505 https://doi.org/10.31209/2018.100000005
IEEE Style
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," Intell. Automat. Soft Comput. , vol. 24, no. 3, pp. 493-505. 2018. https://doi.org/10.31209/2018.100000005