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Call for Paper - May 2015 Edition
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Neural Network based Kannada Numerals Recognition System

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IJCA Proceedings on National Conferecne on Advanced Computing and Communications 2012
© 2012 by IJCA Journal
NCACC - Number 1
Year of Publication: 2012
Authors:
Shreedharamurthy S K
H. R. Sudarshana Reddy

Shreedharamurthy S K and Sudarshana H R Reddy. Article: Neural Network based Kannada Numerals Recognition System. IJCA Proceedings on National Conferecne on Advanced Computing and Communications 2012 NCACC(1):1-4, August 2012. Full text available. BibTeX

@article{key:article,
	author = {Shreedharamurthy S K and H. R. Sudarshana Reddy},
	title = {Article: Neural Network based Kannada Numerals Recognition System},
	journal = {IJCA Proceedings on National Conferecne on Advanced Computing and Communications 2012},
	year = {2012},
	volume = {NCACC},
	number = {1},
	pages = {1-4},
	month = {August},
	note = {Full text available}
}

Abstract

This paper presents a novel approach for feature extraction in spatial domain to recognize segmented (isolated) Kannada numerals using artificial neural networks. Artificial neural systems represent the promising new generation of information processing networks to develop intelligent machines which can be used as classifier. The ability of neural networks to learn by ordinary experience, as we do, and to take sensitive decisions give them the power to solve problems found intractable or difficult for traditional computation. In this paper, the development of handwritten Kannada numeral recognition system using spatial features and neural networks is reported. Handwritten numerals are scan converted to binary images and normalized to a size of 30 x 30 pixels. The features are extracted using spatial co ordinates and are classified successfully using the feed forward neural network classifier.

References

  • K V Prema_ and N V Subbareddy- Two-tier architecture for unconstrained handwritten character recognition-Sadhana Vol. 27, Part 5, October 2002, pp. 585-594.
  • Hyun-Chul Kim, Daijin Kim, Sung Yang Bang-A numeral character recognition using PCA mixture model, pattern recognition letters, Vol 23, 2002, pp. 103-111
  • G Y Chen, T D Bui, A. Krzyzak-Contour based numeral recognition using mutiwavelets and neural networks, pattern recognition letters, Vol 36, 2003, pp. 1597-1604
  • Rejean Plamondon, Sargur. N. Srihari, On-line and Off-line Handwriting Recognition: A Comprehensive survey, IEEE Trans,Pattern Analysis and Machine Intelligence, vol 22, no 1, pp 63-79,Jan 2000
  • Claus Bahlmann-Directional features in online handwriting recognition, pattern recognition letters, Vol 39, 2006, pp. 115-125
  • Oivind Due Trier, Anil. K. Jain and Torfinn Taxt,-Feature Extraction Methods for Character Recognition – A Surve, July 1995.
  • Alexander Goltsev, Dmitri Rachkovskij-Combination of the assembly neural network with a perceptron for recognition of handwritten digits arranged in numeral strings, pattern recognition letters, Vol 38, 2005, pp. 315-322
  • Bailing Zhang, Minyue Fu, Hong Yan-A nonlinear neural network model of mixture of local principal component analysis: application to handwritten digits recognition, pattern recognition letters, Vol 34, 2001, pp. 203-214
  • Cheng-Lin Liu, Kazuki Nakashima, Hiroshi Sako, Hiromichi Fujisawa, Handwritten digit recognition: investigation of normalization and feature extraction techniques, Jun 2003
  • R. Jagadeesh Kannan and R. Prabhakar- Off-Line Cursive Handwritten Tamil Character Recognition- WSEAS TRANSACTIONS on SIGNAL PROCESSING- ISSN: 1790-5052 Issue 6, Volume 4, June 2008.
  • G. G. Rajput, Rajeswari Horakeri, Sidramappa Chandrakant- Printed and Handwritten Mixed Kannada Numerals Recognition Using SVM- IJCSE- Vol. 02, No. 05, 2010, 1622-1626
  • N. Arica and F. T. Yarman_Vural-One dimensional representation of two dimensional information for HMM based handwriting recognition, Pattern recognition letters, vol-21(2000)583-592