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Survey on various Improved Feature Extraction and Classification Techniques on Handwritten Marathi Character Recognition

Published on July 2015 by Parshuram M. Kamble, Ravindra S. Hegadi
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National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
Foundation of Computer Science USA
NCKITE2015 - Number 3
July 2015
Authors: Parshuram M. Kamble, Ravindra S. Hegadi
1f77a663-d74f-491f-bc20-e0136d30896e

Parshuram M. Kamble, Ravindra S. Hegadi . Survey on various Improved Feature Extraction and Classification Techniques on Handwritten Marathi Character Recognition. National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015). NCKITE2015, 3 (July 2015), 37-40.

@article{
author = { Parshuram M. Kamble, Ravindra S. Hegadi },
title = { Survey on various Improved Feature Extraction and Classification Techniques on Handwritten Marathi Character Recognition },
journal = { National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015) },
issue_date = { July 2015 },
volume = { NCKITE2015 },
number = { 3 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 37-40 },
numpages = 4,
url = { /proceedings/nckite2015/number3/21498-2669/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%A Parshuram M. Kamble
%A Ravindra S. Hegadi
%T Survey on various Improved Feature Extraction and Classification Techniques on Handwritten Marathi Character Recognition
%J National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%@ 0975-8887
%V NCKITE2015
%N 3
%P 37-40
%D 2015
%I International Journal of Computer Applications
Abstract

Optical Character recognition of Indian scrip is challenging task, due to they have various type of shapes, curves and lines. We found variation in dataset of same writer in same time of same characters. In survey we found the researcher used various morphological, spatial domain techniques in pre-processing to remove noise, slant and skew of handwritten Marathi character. In recently Marathi character feature are extracted using some statistical, geometrical and structural methods. They are applied to classify k-nn, SVM, ANN, Decision Tree classification Methods for handwritten Marathi character classification.

References
  1. K. V. Kale, P. D. Deshmukh, Y Shriniwas, V Chavan and Majharoddin M. Kazi, " Zernike moment Feature Extraction for Handwrittem Devnagari( Marathi) Compound Character Recognition", International Journal of Advanced Reserch in Artificial Intelligence, Vol. 3, No. 1, 2014.
  2. Nafiz Arica, Fatos T. and Yarman Vural. "An Overview of Character Recognition Focused on off-line handwriting", C99-06-C-203, IEEE, 2000.
  3. R. M. K. and Sinha, "Rule Based Contextual Post- processing for Devnagari Tex Recognition", Pattern Recognition, Vol. 20, No. 5, pp. 475-485, 1987.
  4. S. Kumar and C. Sinha, " A Study of Zernike Moments and its use in Devnagari Handwritten Character Recognition", Int. Conf. on Cognition and Recognition, pp-514-520, 2005.
  5. U. Pal and B. B. Chaudhuri, " Indian Script Character recognition: A survay", Pattern Recognition, Vol. 37, PP. 1887-1899, 2004.
  6. B. V. Dhandra and Mallikarjun Hangarge, "Global and Local Features Based Handwritten Text Words and Numerals Script Identification", Intl. Conf. on Computational Intelligence and Multimedia Applications, PP 471-475. 2007.
  7. Latesh Malik and P. S. Deshpande, "Recognition of printed Devnagari characters with regular expression in finite state models", International workshop on machine intelligence research, GHRCE Nagpur, India, 2009.
  8. M. Hanmandlu and Pooja Agrawal, "A Structural Approach for Segmentation of Handwritten Hindi Text", International Conference on Cognition and Recognition. pp 589-597. 2007.
  9. Muharrem Mercimek, Kayhan Gulez and Tarik Veli umcu, "Real object recognition using moment invariants", Sadhana Vol. 30, Part 6, pp. 765–775, Dec. 2005.
  10. Harikesh Singh, R. K. Sharma, "Moment in Online Handwritten Character Recognition", National Conference on Challenges & Opportunities in Information Technology (COIT-2007) Gobindgarh. March 23, 2007. ,
  11. R. S. Hegadi and P. M. Kamble, "Recognition of marathi handwritten numerals using multi-layer feed-forward neural network," in World Congress on Computing and Communication Technologies (WCCCT),. IEEE, 2014, pp. 21–24.
  12. P. M. Kamble and R. S. Hegadi, "Handwritten marathi basic character recognition using statistical method," in Emerging Research in Computing, Information, Communication and Applications. Elsevier 2014, Vol. 3, 2014, pp. 28–33.
  13. Dongre, Vikas J. , and Vijay H. Mankar. "A review of research on Devnagari character recognition. " arXiv preprint arXiv:1101. 2491 (2011).
  14. Kamble P M and Hegadi R S, "Handwritten Marathi Character Recognition Using R-HOG Feature", Elsevier Procedia Computer Science, Vol. 45 pp. 266–274, 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Handwritten Marathi Character Classification Segmentation Feature Extraction.