DocumentCode
2722596
Title
Neural Network Based Offline Tamil Handwritten Character Recognition System
Author
Sutha, J. ; Ramaraj, N.
Author_Institution
Sethu Inst. of Technol., Virudhunagar
Volume
2
fYear
2007
fDate
13-15 Dec. 2007
Firstpage
446
Lastpage
450
Abstract
In this paper we propose an approach to recognize handwritten Tamil characters using a multilayer perceptron with one hidden layer. The feature extracted from the handwritten character is Fourier descriptors. Also an analysis was carried out to determine the number of hidden layer nodes to achieve high performance of backpropagation network in the recognition of handwritten Tamil characters. The system was trained using several different forms of handwriting provided by both male and female participants of different age groups. Test results indicate that Fourier descriptors combined with backpropagation network provide good recognition accuracy of 97% for handwritten Tamil characters.
Keywords
Fourier transforms; backpropagation; feature extraction; handwritten character recognition; multilayer perceptrons; Fourier descriptors; backpropagation network; feature extraction; multilayer perceptron; neural network; offline Tamil handwritten character recognition system; Backpropagation; Character recognition; Computational intelligence; Feature extraction; Handwriting recognition; Histograms; Multimedia systems; Natural languages; Neural networks; Smoothing methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on
Conference_Location
Sivakasi, Tamil Nadu
Print_ISBN
0-7695-3050-8
Type
conf
DOI
10.1109/ICCIMA.2007.86
Filename
4426737
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