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IJSTR >> Volume 1 - Issue 8, September 2012 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Artificial Neural Network Application In Letters Recognition For Farsi/Arabic Manuscripts

[Full Text]

 

AUTHOR(S)

Farhad Soleimanian Gharehchopogh, Ezzat Ahmadzadeh

 

KEYWORDS

Keywords:- Artificial Neural Networks, Back Propagation Algorithm, Letter Recognition, Multi-Layer Perceptron, Farsi/Arabic, Manuscripts

 

ABSTRACT

Abstract:- Letter recognition for manuscript is one of the categories that has been deliberated in recent years and has many applications. Considering variety of hand writings correct recognition of manuscript letter has many difficulties. In literature various algorithms has been used to letter recognition for manuscript in different languages. Regarding to artificial neural networks (ANNs) abilities in machine learning, parallel processing, flexibility and pattern recognition it would be a convenient method to be used in this field. In this paper, we proposed an ANN based algorithm to letter recognition for Farsi/Arabic manuscript. Finally, we illustrate that proposed method is one of the best method to be used in letter recognition for Farsi/Arabic manuscript.

 

REFERENCES

[1] A. Meisels, A. Kandel, G. Gecht , “Entropy, and the recognition of fuzzy letters”, Fuzzy Sets and Systems, Volume 31, Issue 3, 20 July1989, Pages297-309.

[2] S.N. Srihari, “Recognition of handwritten and machine-printed text for postal address interpretation”, Pattern Recognition Letters, Volume 14, Issue 4, April 1993, Pages 291-302.

[3] B.A. Blesser, T.T. Kuklinski, R.J. Shillman “Empirical tests for feature selection based on a psychological theory of character recognition”, Pattern Recognition, Volume 8, Issue 2, April1976,Pages 77-85.

[4] P.S. Wang, “A new character recognition scheme with lower ambiguity and higher recognizability”, Recognition Letters, Volume 3, Issue 6, December 1985,Pages431-436

[5] H.J. Kim, J.W. Jung, S.K. Kim, “On-line Chinese character recognition using ART-based stroke classification” Pattern Recognition Letters, Volume 17, Issue 12, 25 October 1996, Pages 1311-1322.

[6] S. Mozaffari, K. Faez, V. Margner, H. El-Abed, “Lexicon reduction using dots for off-line Farsi/Arabic hand written word recognition” Pattern Recognition Letters, Volume 29, Issue 6, 15 April 2008, Pages 724-734.

[7] A. Vinciarelli, J. Luettin, “A new normalization technique for cursive handwritten words”, Pattern Recognition Letters, Vol. 22, Iss. 9, July 2001, pp. 1043-1050.

[8] F. S. Gharehchopogh, “Neural Network Application in Software Cost Estimation: A Case Study”, 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA 2011), pp. 69-73, IEEE, Istanbul, Turkey, 15-18 June 2011.

[9] S.Sathasivam, ”Application of neural networks in predictive data mining”, 2nd international conference on business and economic research (2nd icber 2011),March 2011, Pages 371-376.

[10] M. Kang, D. P. Brown, “A Model Learning Adaptive Function Neural Network Applied Handwritten Digit Recognition”, Information Sciences, Special Issue on Industrial Applications of Neural Networks, Vol. 178, Iss. 20, 15 October 2008, pp. 3802-3812.

[11] W. Gao,”New Evolutionary Neural Networks”, International Conference on Neural Interface and Control, Wuhan Polytech. Univ., China, Pages 167-171, May 26-28 (2005).

[12] [12] Manish Mangal and Manu Pratap Singh, “Patterns Recalling Analysis of Hopfield Neural Network with Genetic Algorithms”. Accepted for publication in International Journal of Innovative Computing, Information and Control, (JAPAN), 2007.

[13] A. Kochari, J. Azimi, A. Mohabadi, ”Letter Recognition Using Fuzzy Logic”, Second International Conference of Information Technology (Language : Farsi)

[14] S. Jaberian, ” Letter Recognition Using Pen Movement for Farsi Manuscript”, MS.c Degree, Computer Department of Isfahan, Winter 1376(Language :Farsi).

[15] J.H.Chiang, “Crucial Combinations for the Recognition of Handwritten Letters”, Pattern Recognition Letters, Vol. 21, Iss. 10, September 2000, Pages: 873-898.

[16] J. H Chiang, “A hybrid neural network model in handwritten word recognition” Original Research Article Neural Networks, Vol. 11, Iss. 2, 31 March 1998, Pages: 337-346.

[17] A. Amin, “Recognition of hand-printed characters based on structural description and inductive logic programming” Pattern Recognition Letters, Vol. 24, Iss. 16, December 2003, Pages: 3187-3196.

[18] F. Mahmoudi, M. Mirzashaeri, E. Shahamatnia, S. Faridnia, “A Novel Handwritten Letter Recognizer Using Enhanced Evolutionary Neural Network”, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2009, LNIcst 8, Pages: 1-9, 2009.

[19] Mangal, M., Singh, M.P, “Handwritten English Vowels Recognition Using Hybrid Evolutionary Feed-Forward Neural Network”, Malaysian Journal of Computer Science, Vol. 19, Iss. 2, Pages: 169–187, 2006.