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Reseach Article

Arabic Numerals Recognition based on an Improved Version of the Loci Characteristic

by Ouafae EL Melhaoui, Mohamed El Hitmy, Fairouz Lekhal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 24 - Number 1
Year of Publication: 2011
Authors: Ouafae EL Melhaoui, Mohamed El Hitmy, Fairouz Lekhal
10.5120/2912-3830

Ouafae EL Melhaoui, Mohamed El Hitmy, Fairouz Lekhal . Arabic Numerals Recognition based on an Improved Version of the Loci Characteristic. International Journal of Computer Applications. 24, 1 ( June 2011), 36-41. DOI=10.5120/2912-3830

@article{ 10.5120/2912-3830,
author = { Ouafae EL Melhaoui, Mohamed El Hitmy, Fairouz Lekhal },
title = { Arabic Numerals Recognition based on an Improved Version of the Loci Characteristic },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 24 },
number = { 1 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume24/number1/2912-3830/ },
doi = { 10.5120/2912-3830 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:09:53.232953+05:30
%A Ouafae EL Melhaoui
%A Mohamed El Hitmy
%A Fairouz Lekhal
%T Arabic Numerals Recognition based on an Improved Version of the Loci Characteristic
%J International Journal of Computer Applications
%@ 0975-8887
%V 24
%N 1
%P 36-41
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The present work is concerned with handwritten and printed numeral recognition based on an improved version of the loci characteristic method (CL) for extracting the numeral features. After a preprocessing of the numeral image, the method divides the image into four equal parts and applies the traditional CL to each of the parts. The recognition rate obtained by this method is improved indicating that the numeral features extracted contain more details. Numeral recognition is carried out in this work through k nearest neighbors and multilayer perceptron techniques.

References
  1. Reza Ebrahimpour, Mohammad R. Moradian, Alireza Esmkhani,Farzad M. Jafarlou . 2009. Recognition of Persian handwritten digits using Characterization Loci and Mixture of Experts. International Journal of Digital Content Technology and its Applications. Volume 3, Number 3.
  2. H.Glusksmen. 1967. Classification of mixed-font alphabetic by characteristic loci. Digest of 1st Annual IEEE Comp. Conf, pp.138-141.
  3. Dupré, X. 2003. Contributions à la reconnaissance de l'écriture cursive à l'aide de modèles de Markov cachés. Thèse, Université René Descartes - Paris.
  4. Hamid Reza Boveiri, 2010. Persian Printed Numerals Classification Using Extended Moment Invariants. World Academy of Science, Engineering and Technology 63.
  5. Hatem M.R. Abou-zeid, 2003. Computer Recognition of Unconstrained Handwritten Numerals. The 46th IEEE International Midwest Symposium on Circuits and Systems. Cairo-Egypt.
  6. Farès Menasri, Nicole Vincent, Emmanuel Augustin. "Reconnaissance de chiffres farsi isolés par réseau de neurones à Convolutions". Actes du dixième Colloque International Francophone sur l’Écrit et le Document.
  7. Reza Ebrahimpour, and Samaneh Hamedi. 2009. Handwritten Digit Recognition by Multiple Classifier Fusion based on Decision Templates Approach. World Academy of Science, Engineering and Technology 57.
  8. M. Soryani, and N. Rafat. 2007. Application of Genetic Algorithms to Feature Subset Selection in a Farsi OCR. International Journal of Engineering and Applied Sciences .
  9. Benne R.G.1, Dhandra B.V.1 and Mallikarjun Hangarge. 2009. Tri-scripts handwritten numeral recognition: a novel approach". Advances in Computational Research, ISSN: 0975–3273, Volume 1, Issue 2, pp: 47-51.
  10. G. G. Rajput, S. M. Mali. 2010. Marathi Handwritten Numeral Recognition using Fourier Descriptors and Normalized Chain Code. IJCA Special Issue on Recent Trends in Image Processing and Pattern Recognition” RTIPPR.
  11. Farès Menasri. 2008. Contributions à la reconnaissance de l'écriture arabe manuscrite. Thèse.
  12. ROBERTO GIL-PITA, XIN YAO. 2008. EVOLVING EDITED k-NEAREST NEIGHBOR CLASSIFIERS. International Journal of Neural Systems, Vol. 18, No. 6, pp: 459–467.
  13. Vicente Cerverón and Francesc J. Ferri. 2001. Another Move toward the Minimum Consistent Subset: A Tabu Search Approach to the Condensed Nearest Neighbor Rule". IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, Volume. 31, N°. 3.
  14. Ludmila I. Kuncheva. 1995. Editing for the k-nearest neighbors rule by a genetic algorithm. Elsevier, Pattern Recognition Letters 16, pp: 809-814.
  15. K. Faez, E. Khotanzad, and M. H. Shiralishahreza, 1995. Recognition of Persian Handwritten Letters and Digits Using Pseudo-Zernike Moments and Neural Networks. in Proc. 3rd Iranian Conf. on Electrical Engineering, Tehran, pp. 231-240.
  16. DERDOUR Khedidja. 2009. Reconnaissance de formes du chiffre arabe imprimé : Application au code à barre d’un produit. Mémoire.
  17. Rajashekararadhya, P. Vanaja Ranjan. 2009. Handwritten numeral recognition of Canada script. Proceeding of the international workshop on machine intelligence research labs.
  18. Marc Parizeau, 2004. Réseaux de neurones. Livre
  19. Harifi, A.Aghagolzadeh. 2004. A New Pattern for Handwritten Persian/Arabic, Digit Recognition. International Journal of Information Technology. Vol 1, N° 4.
  20. Alberto Sanfeliu, José Francisco Martínez Trinidad, Jesús Ariel Carrasco Ochoa. 2004. Progress in pattern recognition, image analysis and applications. 9th Iberoamerican Congress on Pattern Recognition, CIARP, Puebla, Mexico. Proceedings. Lecture Notes in Computer Science 3287 Springer 2004, ISBN 3-540-23527-2
  21. J.Pradeep, E.Srinivasan, S.Himavathi. 2010. Diagonal Feature Extraction Based Handwritten Character System Using Neural Network. International Journal of Computer Applications (0975 – 8887). Vol 8, N°.9, pp: 17-22.
  22. Jiawei Han, Micheline Kamber. “Data mining: concepts and techniques”. livre
Index Terms

Computer Science
Information Sciences

Keywords

Handwritten and printed numeral recognition loci characteristic features extraction preprocessing k nearest neighbors multilayer perceptron