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Reseach Article

Special Approach for Recognition of Handwritten MODI Script’s Vowels

Published on September 2012 by D. N. Besekar
National Conference "MEDHA 2012"
Foundation of Computer Science USA
MEDHA - Number 1
September 2012
Authors: D. N. Besekar
a78cfab9-86ff-4cd3-91c2-b9d89f78004f

D. N. Besekar . Special Approach for Recognition of Handwritten MODI Script’s Vowels. National Conference "MEDHA 2012". MEDHA, 1 (September 2012), 48-52.

@article{
author = { D. N. Besekar },
title = { Special Approach for Recognition of Handwritten MODI Script’s Vowels },
journal = { National Conference "MEDHA 2012" },
issue_date = { September 2012 },
volume = { MEDHA },
number = { 1 },
month = { September },
year = { 2012 },
issn = 0975-8887,
pages = { 48-52 },
numpages = 5,
url = { /proceedings/medha/number1/8679-1023/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference "MEDHA 2012"
%A D. N. Besekar
%T Special Approach for Recognition of Handwritten MODI Script’s Vowels
%J National Conference "MEDHA 2012"
%@ 0975-8887
%V MEDHA
%N 1
%P 48-52
%D 2012
%I International Journal of Computer Applications
Abstract

The ambient study had been performed on foreign language like Arebic, chineses Japanese etc. efforts on India script is still immature. OCR of MODI script language is still not available as it is cursive type and old language i. e. Shivkalin and Peshwekalin. the challenges of recognition of character is even high in handwritten domain , due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten MODI script Vowels. the proposed method uses chain code and image centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification.

References
  1. Otsu. N, "A threshold selection method from gray levelhistograms", IEEE Trans. Systems, Man and Cybernetics, vol. 9, pp. 62-66, 1979
  2. Trier. O. D, Jain. A. K and Taxt. J, "Feature extractionmethods for character recognition - A survey", PatternRecognition, vol. 29, no. 4, pp. 641-662, 1996.
  3. Freeman, H. , On the encoding of arbitrary geometricconfigurations IRE Trans. on Electr. Comp. or TC(10),No. 2, June, 1961, pp. 260-268
  4. Rafael C. Gonzalez, Richard E. Woods,"Digital Image Processing (2nd Edition) ",PHI
  5. Martin Fodslette Møller, "A scaled conjugate gradient algorithm for fast supervised learning", Neural Networks, Elsevier, Volume 6, Issue 4, 1993, pp 525
  6. G. G. Rajput, Rajeswari Horakeri, Sidramappa Chandrakant, "Printed and handwritten mixed Kannada numerals recognition using SVM", International Journal on Computer Science and Engineering Vol. 02, No. 05, 2010, 1622-1626
  7. S. V. Rajashekararadhya, Vanaja Ranjan P, "Zone-based hydrid feature extraction algorithm for handwritten numeral recognition of four Indian scripts",Proceedings of the 2009 IEEE International Conference on Systems, Man and Cybernetics, San Anonio,TX, USA- October, 2009.
  8. Lajish V. L. , "Handwritten character recognition using gray scale based state space parameters and class modular NN",Proc. 4th Int. National conf. on Innovations in IT, 2007, 374 – 379.
  9. Bindu Philip, R. D. Sudhakaer Samuel, "Preferred computational approaches for the recognition of different classes of printed Malayalam characters using hierarchical SVM classifiers", International Journal of Computer Applications (0975-8887) vol 1-No. 16,2010
  10. Xiaoyu Zhao,Zheru Chi and D. Feng, "An Improved Algorithm for Segmenting and Recognizing Connected Handwritten Characters", 11th Int. Conf. on control, Automation, Robotics and Vision, Singapore, IEEE,7-10 Dec. 2010.
  11. Sari Dewi Budiwati,Joko Haryatno, E. M. Dharma, "Japanese Character(Kana) Pattern Recognition Application Using Neural Network", IEEE trans. , 2011
  12. Nicolas Passat, B. Naegel, F. Rousseau, M. Koob, "Interactive Segmentation based on Component-trees", Jrnl. Pattern Recognition, Vol. 44,pp. 2539-2554, 2011
  13. U. Pal, P. P. Rao, N. Tripathy, Josep LIados, "Multi- oriented Bangla and Devnagari text recognition", Jrnl. Pattern Recognition, Vol. 43,pp. 4124-4136, 2010
  14. U. Pal, M. Mitra and B. B. Chaudhuri, "Multi-Skew Detection of Indian Script Documents", IEEE trns. , 2001
  15. R. J. Kannan, R. Prabhakar and R. Suresh, "Off-line Cursive Handwritten Tamil Character Recognition", IEEE trns. , Int. Conf. on Security Technology, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Modi Script Handwritten Character Recognition Chain Code Feed Forword Networ Image Processing