CFP last date
22 April 2024
Reseach Article

On-line Handwritten Arabic Character Recognition using Artificial Neural Network

by Khaoula Addakiri, Mohamed Bahaj
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 55 - Number 13
Year of Publication: 2012
Authors: Khaoula Addakiri, Mohamed Bahaj
10.5120/8819-2819

Khaoula Addakiri, Mohamed Bahaj . On-line Handwritten Arabic Character Recognition using Artificial Neural Network. International Journal of Computer Applications. 55, 13 ( October 2012), 42-46. DOI=10.5120/8819-2819

@article{ 10.5120/8819-2819,
author = { Khaoula Addakiri, Mohamed Bahaj },
title = { On-line Handwritten Arabic Character Recognition using Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 55 },
number = { 13 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 42-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume55/number13/8819-2819/ },
doi = { 10.5120/8819-2819 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:57:10.658370+05:30
%A Khaoula Addakiri
%A Mohamed Bahaj
%T On-line Handwritten Arabic Character Recognition using Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 55
%N 13
%P 42-46
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an efficient approach for the recognition of on-line Arabic handwritten characters is presented. The method employed involves three phases: First, pre-processing in which the original image is transformed into a binary image . Second , training neural networks with feed-forward back propagation algorithm . Finally, the recognition of the character through the use of Neural Network techniques. The proposed approach is tested on 1400 different characters written by ten users. Each user wrote 28 Arabic characters five times in order to get different writing variations. Experiment results showed the effectiveness of our approach for recognizing handwritten Arabic characters.

References
  1. Vaseghi. B. , Alirezaee. Sh. , "Off-line Farsi/Arabic Handwritten word recognition using vectorquantization and hidden markov model," Proceedings of the 12th IEEE International Multitopic Conference, 978-1-4244-2824-3/08/$25. 00
  2. Dehghan M. , Faez K. , Ahmadi M. and Shridhar M. , "Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMM", Pattern Recognition, vol. 34, no 5, pp. 1057-1065, 2001
  3. Chen M. Y. , Kundu A. , Srihari S. N. , "Variable Duration Hidden Markov and Morphological Segmentation for Handwritten Word Recognition," IEEE Transactions on Image Processing, Vol. 4, No. 12, PP. 1675-1688, 1995.
  4. Kim G. , Govindaraju V. , "A Lexicon Driven Approach to Handwritten Word Recognition for Real-Time Applications," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 4, PP. 366-379, 1997.
  5. Guillevic D. , Suen C. Y. , "HMM-KNN Word Recognition Engine for Bank Cheque Processing,"Proceedings of International Conference on Pattern Recognition, Vol. 2, PP. 1526-1529, Brisebane, Ausrtalia, August 1998.
  6. Adnan Amin,"Off-Line Arabic Character Recognition: The State of The Art", Pattern Recognition,Vol. 31, No. 5, 1998, pp. 517-530.
  7. Amin, A. , Al-Sadoun, H. , Fischer, S. ,"Hand-printed Arabic character recognition system using an artificial network". Pattern Recognition, Vol. 29, No. 4, pp. 663 -675, 1996.
  8. Abdulkadr, A. , "Two-tier approach for Arabic offline handwriting recognition". In: Proc. 10th Internet. Workshop on Frontiers in Handwriting Recognition (IWFHR), pp. 161–166. 2006
  9. Karim Hadjar and Rolf Ingold, "Arabic Newspaper Page Segmentation", proceeding of the seventh international conference on document analysis and recognition, Vol. 2, 2003, pp. 895 - 899.
  10. T. S. El-Sheikh and S. G. El-Taweel, "Real-time Arabic handwritten character recognition", Pattern Recognition, Vol. 23, no. 12 , 1990, pp. 1323-1332.
  11. T. S. El-Sheikh and Ramez M. Guindi, "Computer recognition of Arabic cursive scripts", Pattern Recognition, Vol. 21, no. 4, 1988, pp. 293-302.
  12. F. El-Khaly and M. A. Sid-Ahmed, "Machine recognition of optically captured machine printed Arabic text", Pattern Recognition, Vol. 23, no. 11, 1990, pp. 1207-1214.
  13. Mohamed S. El-Wakil and Amin A. Shoukry, "On-line recognition of handwritten isolated arabic char-acters", Pattern Recognition, Vol. 22, no. 2, 1989, pp. 97-105.
  14. Sabri A. Mahmoud, "Arabic character recognition using Fourier descriptors and character contour en-coding", Pattern Recognition, Vol. 27, no. 6, 1994, pp. 815-824.
  15. A. Cheung, M. Bennamoun, and N. W. Bergmann, "An Arabic optical character recognition system using recognition-based segmentation ", Pattern Recognition, Vol. 34, 2001, pp. 215 - 233.
  16. M. S. Khorsheed, "Recognizing handwritten Arabic manuscripts using a single hidden Markov model", Pattern Recognition Letters, Vol. 24, 2003, pp. 2235-2242.
  17. Neila Mezghani, Mohamed Cheriet, and Amar Mitiche, "Combination of Pruned Kohonen Maps for On-line Arabic Characters Recognition ", In proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003), pp. 900 - 904.
  18. J. H. AlKhateeb, J. Ren, J. Jiang, H. Al-Muhtaseb," Offline handwritten Arabic cursive text recognition using Hidden Markov Models and re-ranking", Pattern Recognition Letters 32 (2011) 1081–1088.
  19. B. Vaseghi, S. Hashemi," Farsi/arabic Handwritten Word Recognition Using Discrete HMM and Self-Organizing Feature Map", International Congress on Informatics, Environment, Energy and Applications-IEEA 2012 - IPCSIT vol. 38 (2012) .
  20. A. T. Al-Taani, S. Al-Haj," Recognition of On-line Arabic Handwritten Characters Using Structural Features", Journal of Pattern Recognition Research 1 (2010) 23-37.
  21. M. Meyer, G. Pfeiffer, "Multilayer perceptron based decision feedback equalizers for channels with intersymbol interference,". IEEE Transactions,Vol 140, No 6, pp 420-424, Dec 1993.
  22. M. Ibnkahla, Signal Processing for Mobil Communications Handbook, Ed. Boca Raton, FL: CRC Press, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Pattern Recognition Neural Networks Arabic Handwritten