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Reseach Article

Recognition of Farsi Letter using Hidden Markov Model

by Sadegh Zarezade, Abbas Akkasi, Ayoob Maher, Yalda Namdar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 125 - Number 1
Year of Publication: 2015
Authors: Sadegh Zarezade, Abbas Akkasi, Ayoob Maher, Yalda Namdar
10.5120/ijca2015905791

Sadegh Zarezade, Abbas Akkasi, Ayoob Maher, Yalda Namdar . Recognition of Farsi Letter using Hidden Markov Model. International Journal of Computer Applications. 125, 1 ( September 2015), 43-45. DOI=10.5120/ijca2015905791

@article{ 10.5120/ijca2015905791,
author = { Sadegh Zarezade, Abbas Akkasi, Ayoob Maher, Yalda Namdar },
title = { Recognition of Farsi Letter using Hidden Markov Model },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 125 },
number = { 1 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 43-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume125/number1/22400-2015905791/ },
doi = { 10.5120/ijca2015905791 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:14:54.955821+05:30
%A Sadegh Zarezade
%A Abbas Akkasi
%A Ayoob Maher
%A Yalda Namdar
%T Recognition of Farsi Letter using Hidden Markov Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 125
%N 1
%P 43-45
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Letter recognition is taken from optical character recognition (OCR). Some of the applications like devices which read postal code and checks are limited to recognition of numbers and need high speed and accuracy. In current paper the combination of two powerful method i.e. hidden Markov model will be used. Other models are used only in recognition of English words in learning using online method. The accuracy of recognition is 93% for Ifn/Farsi Database.

References
  1. C.-L.Liu and C.Y.Suen. A new benchmark on the recognition of handwritten bangla and farsi numeral characters.Pattern Recognition, In press, 2008.
  2. W.M. Pan, T.D. Bui, and C.Y. Suen : Isolated Handwritten Farsi numerals Recognition Using Sparse And Over-Complete Representations, 2009 10th International Conference on Document Analysis and Recognition
  3. Yasemin Altun and Ioannis Tsochantaridis and Thomas Hofmann: Hidden Markov Support Vector Machines, Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003), Washington DC, 2003.
  4. Christopher M. Bishop: Pattern Recognition and Machine Learning, 2006 Springer ScienceBusiness Media, LLC
  5. Usama Fayyad: A Tutorial on Support Vector Machines for Pattern Recognition, Data Mining and Knowledge Discovery, 2, 121–167 (1998)
  6. Ahmad A.R, Viard-Gaudin, C. Khalid M: Lexicon-based Word Recognition Using Support Vector Machine and Hidden Markov Model, 2009 10th International Conference on Document Analysis and Recognition
  7. F. Solimanpour, J. Sadri, C.Y. Suen, Standard databases for recognition of handwritten digits, numerical strings, legal amounts, letters and dates in Farsi language, in: Proceedings of the 10th International Workshop on Frontiers of Handwriting Recognition, La Baule, France, 2006, pp. 3–7.
  8. Al-Omari, F., Al-Jarrah, O.: Handwritten Indian numerals recognition system using probabilistic neural networks. Adv. Eng. Inform. 18(1), 9–16 (2004)
  9. Said, F., Yacoub, R., Suen, C.: Recognition of English and Arabic numerals using a dynamic number of hidden neurons. Proc. 5th ICDAR, pp. 237–240, 1999
  10. H. Drucker, B. Shahrary, D.C. Gibbon, “Support vector machines: relevance feedback and information retrieval” ,Information Processing and Management 38, p305-323, 2002
  11. Sherif Abdleazeem and Ezzat El-Sherif: Arabic handwritten digit recognition, IJDAR (2008) 11:127–141
  12. Sameh M.Awaidah, Sabri A.Mahmoud: A multiple feature/resolution scheme to Arabic (Indian) numerals recognition using hidden Markov models, Signal Processing 89 (2009) 1176–1184
  13. H. Soltanzadeh, M. Rahmati, Recognition of Persian handwritten digits using image profiles of multiple orientations, Pattern Recognition Lett. 25 (14) (2004) 1569–1576.
  14. M. Ziaratban, K. Faez, F. Faradji, Language-based feature extraction using template-matching in Farsi/Arabic handwritten numeral recognition, in: Proceedings of the 9th International Conference on Document Analysis and Recognition, vol. 1, Curitiba, Brazil, 2007, pp. 297–301.
Index Terms

Computer Science
Information Sciences

Keywords

Recognition Farsi letters hidden Markov model