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Proceedings Paper

Kannada character recognition system using neural network
Author(s): Suresh D. S. Kumar; Srinivasa Kalyan Kamalapuram; Ajay B. R. Kumar
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Paper Abstract

Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. As there is no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India. In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten Kannada character is resized into 20x30 Pixel. The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different Kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.

Paper Details

Date Published: 14 March 2013
PDF: 5 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 876843 (14 March 2013); doi: 10.1117/12.2011118
Show Author Affiliations
Suresh D. S. Kumar, Channabasaveshwara Institute of Technology (India)
Srinivasa Kalyan Kamalapuram, Channabasaveshwara Institute of Technology (India)
Ajay B. R. Kumar, Channabasaveshwara Institute of Technology (India)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

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