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A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments

Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda


In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.

Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.

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[1] J. Mantas, "An Overview of Character Recognition Methodologies", Pattern Recognition, Vol.19, No.6, 1986, pp.425–430.
[2] S. Mori, C. Y. Suen and K. Yamamoto, “Historical Review of OCR Research and Development”, Proceedings of the IEEE, Vol. 80, No. 7, 1992, pp. 1029-1058.
[3] A. L. Koerich, R. Sabourin, C. Y. Suen & A. El-Yacoubi, "A Syntax Directed Level Building Algorithm for Large Vocabulary Handwritten Word Recognition", In 4th International Workshop on Document Analysis Systems (DAS 2000) , Rio de Janeiro, Brazil, December 2000.
[4] L. S. Oliveira, R. Sabourin, F. Bortolozzi and C. Y. Suen, "A Modular System to Recognize Numerical Amounts on Brazilian Bank checks", 6th International Conference on Document Analysis and Recognition (ICDAR 2001), Seattle-USA, IEEE Computer Society Press, September 10-13, 2001. pp 389-394.
[5] S. Ouchtati, M. Bedda, F. Bouchareb and A. Lachouri “An Off Line System for the Handwritten Numeric Chains Recognition", International Journal of Soft Computing (IJSC), ISSN: 1682-9503, Vol. 1, No. 4, 2006, pp. 279-287.
[6] A. Filatov, N. Nikitin, A. Volgunin, and P. Zelinsky, "The Address Script TM Recognition System for Handwritten Envelopes", In International Association for Pattern Recognition Workshop on Document Analysis Systems (DAS’98), Nagano, Japan, November 4-6 1998, pp. 157–171.
[7] A. El-Yacoubi, "Modélisation Markovienne de L’´écriture Manuscrite Application `a la Reconnaissance des Adresses Postales", PhD thesis, Université de Rennes 1, Rennes, France, 1996.
[8] J. Hu, M. K. Brown and W Turin, “HMM based on-line handwriting recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, October . 1996, pp. 1039-1045.
[9] G. Kim and V. Govindaraju, “A lexicon driven approach to handwritten word recognition for real-time applications”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, April 1997, pp. 366- 379.
[10] R. Buse, Z-Q Liu, and T. Caelli, “A structural and Relational Approach to Handwritten Word Recognition”, IEEE Trans. Systems, Man and Cybernetics, Part-B, Vol. 27, October. 1997, pp. 847-861.
[11] K. Liu, Y. S. Huang and C. Y. Suen, “Identification of fork Points on the Skeletons of Handwritten Chinese Characters,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, October. 1999, pp. 1095-1100.
[12] A. Amin, "Off-Line Arabic Character Recognition – The State of the Art (Review)", Pattern Recognition, vol. 31, No. 5, 1998, pp. 517-530.
[13] M. Redjimi, S. Ouchtati and M. Bedda, “A New off Line System for the Recognition of the Isolated Handwritten Arabic Characters", Asian Journal of Information Technology (AJIT), ISSN: 1682-3915, Vol. 5, No. 8, 2006, pp. 912-918.
[14] S. Ouchtati, L. Bennacer and M. Bedda, “An Off Line System for the Arabic Handwritten Words Recognition ", International Review on Computers and Software (I.RE.CO.S.), ISSN: 1828-6003, Vol. 3, No. 6, 2008, pp. 579-585.
[15] J. Cai and Z-Q Liu, “Integration of Structural and Statistical Information for Unconstrained Handwritten Numeral Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, March 1999, pp. 263-270.
[16] Oivid Due Trier, Anil K. Jain, & Torfinn Taxt, “Feature Extraction Methods for Character Recognition – A Survey”, Pattern recognition, Vol. 29, No. 4, 1996, pp.641-662.
[17] M. Bedda, M. Ramdani et S. Ouchtati., “Sur le Choix d’une Représentation des Caractères Manuscrits Arabes”, Proceeding du 2ème Conférence Internationale Signaux, Systèmes, et Automatique SSA2’99, Université de Blida, Algérie, 10-12 Mai 1999, pp73-84.
[18] F. Grandidier, "Un nouvel Algorithme de Sélection de Caractéristiques Application à la Lecture Automatique de L’écriture manuscrite", thèse de doctorat en génie PH.D, Ecole de Technologie Supérieure, Université du Quèbec Canada, Janvier 2003.
[19] N. Benahmed, “Optimisation des Réseaux de Neurones Pour la Reconnaissance des Chiffres Manuscrits Isolés, Sélection et Pondération des Primitives par Algorithmes Génétiques”, Thèse pour l’obtention de la Maîtrise en Génie de la Production Automatisée, Montréal le 01 Mars 2002.
[20] Salim Ouchtati, Mohammed Redjimi and Mouldi Bedda, “A Set of Features Extraction Methods for the Recognition of the Isolated Handwritten Digits", International Journal of Computer and Communication Engineering (IJCCE), ISSN: 2010-3743, Vol. 3, No. 5, September 2014, pp. 349-355.
[21] S. Ouchtati, M. Redjimi and M. Bedda, “An Offline System for the Recognition of the Fragmented Handwritten Numeric Chains ", International Journal of Future Computer and Communication (IJFCC), ISSN: 2010-3751, Vol. 4, No. 1, February 2015, pp. 33-39.
[22] S. Ouchtati, M. Bedda, and A. Lachouri “Segmentation and Recognition of Handwritten Numeric Chains", Journal of Computer Science (JCS), ISSN: 1549-3636, Vol. 3, No. 4, 2007, pp. 242-248.