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Hand Written Character Recognition Using Twelve Directional Feature Input and Neural Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 3 |
| Year of Publication: 2010 |
| Authors: Dayashankar Singh, Sanjay Kr. Singh, Maitreyee Dutta |
10.5120/78-173
|
Dayashankar Singh, Sanjay Kr. Singh, Maitreyee Dutta . Hand Written Character Recognition Using Twelve Directional Feature Input and Neural Network. International Journal of Computer Applications. 1, 3 ( February 2010), 82-85. DOI=10.5120/78-173
Abstract
In this paper, we have applied a new feature extraction technique to calculate only twelve directional feature inputs depending upon the gradients. Features extracted from handwritten characters are directions of pixels with respect to their neighboring pixels. These inputs are given to a back propagation neural network with one hidden layer and one output layer. An analysis has been also carried out to compare the recognition accuracy, training time and classification time of newly developed feature extraction technique with some of the existing techniques. Experimental result shows that the new approach provides better results as compared to other techniques in terms of recognition accuracy, training time and classification time. The work carried out in this paper is able to recognize all type of handwritten characters even special characters in any language.
References
- Cheng-Lin Liu, "Normalization-Cooperated Gradient Feature Extraction for Handwritten Character Recognition" IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 29, Issue 8, Aug. 2007 Page(s) 1465-1469.
- Hailong Liu, Xiaoqing Ding, "Handwritten character recognition using gradient feature and quadratic classifier with multiple discrimination schemes" Eighth IEEE International Conference on Document Analysis and Recognition, Vol. 1, Page(s): 19-23, August 29-1 Sept., 2005.
- K. Yamada and H. Kami, "Handwritten numeral recognition by multilayered neural network with improved learning algorithm," IJCNN Washington DC, vol. 2, pp. 259-266, 1989.
- S.J. Smith and M.O. Baurgoin, "Handwritten character classification using nearest neighbor in large database," IEEE Trans. on Pattern and Machine Intelligence, vol. 16, pp. 915-919, Oct. 1994.
- Starzyk,J.A.Ansari, " Feedforward neural network for handwritten character recognition", IEEE International Symposium on Circuits and Systems(ISCAS), Volume 6, Page(s) 2884-2887, 1992.
- Sutha.J, Ramraj.N, "Neural Network Based Offline Tamil Handwritten Character Recognition System", IEEE International Conference on Computational Intelligence and Multimedia Application, 2007 Volume 2, 13-15, Dec.2007, Page(s): 446-450, 2007.
- Verma B.K, "Handwritten Hindi Character Recognition Using Multilayer Perceptron and Radial Basis Function Neural Network", IEEE International Conference on Neural Network, vol.4, pp. 2111-2115, 1995.
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