doi: 10.7763/IJMLC.2012.V2.193
Handwritten Arabic Character Recognition Based on Minimal Geometric Features
Majid Harouni1
,
Dzulkifli Mohamad2 ,
Mohd Shafry Mohd Rahim2 ,
Sami M. Halawani3 ,
Mahboubeh Afzali2
- 1Faculty of Computer Science and Information Systems, Universiti Technologi Malaysia, P. O. Box 81310, Skudai, Johor, Malaysia and with the Department of Computer Science, Islamic Azad University, Dolatabad branch, Isfahan, Iran.
- 2UTMViCube Lab, Faculty of Computer Science and Information Systems, Universiti Technologi Malaysia, P. O. Box 81310, Skudai, Johor, Malaysia.
- 3Faculty of Computing and Information Technology, King Abdul Aziz University, Saudi Arabia.
Abstract
On-line handwriting recognition is one of the most successful applications in the area of pattern recognition. Though this field is quite matured, yet the research issues are still challenging, particularly in handwriting character recognition, where the problems are still wide open. The OCR system for printed characters is almost done, though it cannot guarantee for 100% accuracy. However, the research works in recognition of Arabic handwriting are still at the beginning and require more attention. This paper presents the novel on-line Arabic handwriting character recognition. An efficient approach is introduced here to divide it into some particular component. A set of features are extracted from these components, and then encoded for the classification stage. The system classification is implemented by using two processes, i.e. weight initialization in back propagation, and with multilayer perceptron neural network. Finally, the proposed system was tested on a database of Arabic handwritten samples.
Keywords
- Feature
- extraction;
- on-line
- character
- recognition;
- classification
How to Cite
Majid Harouni, Dzulkifli Mohamad, Mohd Shafry Mohd Rahim, Sami M. Halawani, and Mahboubeh Afzali, "Handwritten Arabic Character Recognition Based on Minimal Geometric Features," International Journal of Machine Learning, vol. 2, no. 5, pp. 578-582, 2012. https://doi.org/10.7763/IJMLC.2012.V2.193
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).