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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 5    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 5, May 2011 Edition
Handwritten Character Recognition using Neural Network
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Chirag I Patel, Ripal Patel, Palak Patel
Optical Character Recognition, Artificial Nueral Network, Backpropogation Network, Skew Detection
Objective is this paper is recognize the characters in a given scanned documents and study the effects of changing the Models of ANN. Today Neural Networks are mostly used for Pattern Recognition task. The paper describes the behaviors of different Models of Neural Network used in OCR. OCR is widespread use of Neural Network. We have considered parameters like number of Hidden Layer, size of Hidden Layer and epochs. We have used Multilayer Feed Forward network with Back propagation. In Preprocessing we have applied some basic algorithms for segmentation of characters, normalizing of characters and De-skewing. We have used different Models of Neural Network and applied the test set on each to find the accuracy of the respective Neural Network.
[1] S. Basavaraj Patil, N. V. Subbareddy ‘Neural network based system for script identification in Indian documents’ in Sadhana Vol. 27, Part 1, February 2002, pp. 83–97.

[2] T. V. Ashwin, P. S. Sastry ’A font and size-independent OCR system for printed Kannada documents using support vector machines’ in Sadhana Vol. 27, Part 1, February 2002, pp. 35–58.

[3] Kavallieratou, E.; Fakotakis, N.; Kokkinakis, G.,’ New algorithms for skewing correction and slant removal on word-level

[OCR]’ in Proceedings of ICECS '99.

[4] Simmon Tanner, “Deciding whether Optical Character Recognition is Feasible”.

[5] Matthew Ziegler, “Handwritten Numeral Recognition via Neural Networks with Novel Preprocessing Schemes”.

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