Home   >   CSC-OpenAccess Library   >    Manuscript Information
Recognition of Tifinaghe Characters Using a Multilayer Neural Network
Rachid El Yachi, Mohamed Fakir, Belaid Bouikhalene
Pages - 109 - 118     |    Revised - 01-05-2011     |    Published - 31-05-2011
Volume - 5   Issue - 2    |    Publication Date - May / June 2011  Table of Contents
character recognition, neural network, image analysis
In this paper, we present an off line Tifinaghe characters recognition system. Texts are scanned using a flatbed scanner. Digitized text are normalised, noise is reduced using a median filter, baseline skew is corrected by the use of the Hough transform, and text is segmented into line and lines into words. Features are extracted using the Walsh Transformation. Finally characters are recognized by a multilayer neural network.
CITED BY (10)  
1 EL ayachi, r., oujaoura, m., fakir, m., & minaoui, B. Code Braille et la reconnaissance d’un document écrit en Tifinagh.
2 Es-Saady, Y., Amrouch, M., Rachidi, A., El Yassa, M., & Mammass, D. International Journal of Scientific & Engineering Research, Volume 5, Issue 4, April-2014 1177 ISSN 2229-5518 Handwritten Tifinagh Character Recognition Using Baselines Detection Features.
3 Rachidi, A., Eddahibi, M., Essaady, Y., & Amrouch, M. Amazigh Characters Automatic Recognition: Overview and Prospects.
4 Es-Saady, Y., Amrouch, M., Rachidi, A., El Yassa, M., & Mammass, D. Handwritten Tifinagh Character Recognition Using Baselines Detection Features. International Journal of Scientific & Engineering Resesarch (IJESR), 5(4).
5 Rachidi, A. Reconnaissance automatique de caractères et de textes amazighes: état des lieux et perspectives.
6 Suria, o. (2014). pengenalan notasi balok menggunakan segmentasi dan jaringan syaraf tiruan untuk menghasilkan nada berirama berbasis ios(Doctoral dissertation, UAJY).
7 Aharrane, n., el moutaouakil, k., & satori, k. statistical methods for amazigh ocr.
8 Es-Saady, Y., Amrouch, M., Rachidi, A., El Yassa, M., & Mammass, D. Réalisation d’un OCR pour l’écriture Amazighe imprimée.
9 El Ayachi, R., Fakir, M., & Bouikhalene, B. (2012). Transformation de Fourier et moments invariants appliqués à la reconnaissance des caractères Tifinaghe. Revu, 31.
10 Es Saady, Y. (2012). Contribution au développement d'approches de reconnaissance automatique de caractères imprimés et manuscrits, de textes et de documents Amazighes.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 iSEEK 
5 Scribd 
6 SlideShare 
7 PdfSR 
A. Sehad, L. Mezai, M.T. Laskri, M. Cheriet, Détection de l’inclinaison des documents arabes imprimés.
Alnsour, A.J. and L.M. Alzoubady, 2006. Arabichandwritten characters recognized by neocognitron artificial neural network. J. Pure Appl. Sci., 3: 1- 17.
Asiri, A. and M.S. Khorsheed, 2005. Automatic processing of handwritten Arabic forms using neural networks. Proceeding of the World Academy of Science, Engineering and Technology, Aug. 2005, pp: 313-317.
Attila Fazekas and Andras Hajdu Recognizing Type set Documents using Walsh , JCITCIT 9, 2-2001, 101-112.
Ch. Choisy and A. Belaid, Cross- learning in analytic word recognition without segmentation, in Int. Journal on documentAnal. & Recognition IJDAR, 4(4): 281-289, 2002.
D. J. Burr, A Normalizing Transform For Cursive Script Recognition,Proc. 6th Int. J. Conf. on Pattern Recognition Munich (1982), pp. 1027–1030
Hadjar, K. and R. Ingold, 2003. Arabic newspaper segmentation. Proceeding of 7th International Conference on Document Analysis and Recognition, Aug. 3-6, IEEE Computer Society, pp: 895-899.
Hamza, Ali A. Back Propagation Neural Network Arabic Characters Classification Module Utilizing Microsoft Word; Journal of Computer Science 4 (9): 744-751, 2008.
Ibrahim S. I. Abuhaiba, Arabic Font Recognition Using Decision Trees Built From Common Words, JCIT-CIT 13, 3-2005, 211-223.
M. Blumenstein & C. K. Cheng & X. Y. Liu, 2002, New Preprocessing Techniques for Handwritten Word Recognition, in Proceedings of the Second IASTED International Conference on Visualization, Imaging and Image Processing (VIIP 2002), ACTA Press, Calgary, pp. 480-484.
M. Fakir and C. Sodeyama, Recognition of Arabic printed Scripts by Dynamic Programing Matching Method, IECICE Trans. Inf & Syst, Vol. E76- D, No.2 Feb. [4]. M. FAKIR, Reconnaissance des Caractères Arabes Imprimés, Thesis, 2001, pp : 28-36, semlalia faculty of science Morocco, 2001. pp: 31-37,1993.
M. Fakir, B. Bouikhalene and K. Moro, Skeletonization Methods Evaluation for the Recognition of PrintedTifinaghe characters, SITCAM’09, Agadir-Maroc.
M. K. Brown, pre-processing techniques for cursive word recognition, Pattern Recognition, Vol.13, N°.5, pp: 447-451, 1983.
M.Amrouch, Y. Es saady, A. Rachidi, M. El Yassa and D. Mammass, Printed Amazigh Character Recognition by a Hybrid Approach Based on Hidden Markov Models and the Hough Transform, 978-1-4244-3757-3/09/$25.00 ©2009 IEEE.
N.Mezghani A.Cheret N.Mitiche, Bayes classification of online arabic characters by Gibbs modeling of class conditional densities, IEEE Trans PAMI Vol 30, issue 7, pp: 1121-1131, july 2008.
R. M. Bozinovic and S. N. Shihari, Off Line Cursive Script Word Recognition, IEEE Trans.Pattern Anal. Mach. Intell. PAMI 11, 1989, pp. 68- 83.
Sarhan A.M. and O. Helalat, 2007. Arabic character recognition using ann networks and statistical analysis. Proceeding of European and Mediterranean Conference on Information Systems, June 24-26, Polytechnic University of Valencia, pp: 1-9.
Standardisation Amazighe (Actes du organisé par le centre de l’Aménagement Linguistique, Rabat, 8-9, décembre 2003
Y. Es saady, M.Amrouch, A. Rachidi, M. El Yassa and D. Mammass, Reconnaissance de caractères Amazighes Imprimés par le Formalisme des Automates à états finis, SITCAM’09, Agadir-Maroc.
Y.X. Gu et al, Application of a multilayer tree in computer recognition of Chinese character, IEEE Trans. On PAMI-5, N°.1, pp: 83-89, 1983.
Professor Rachid El Yachi
Faculty of science and technics - Morocco
Professor Mohamed Fakir
- Morocco
Mr. Belaid Bouikhalene
- Morocco