Recognition of Isolated Handwritten Characters of Gurumukhi Script using Neocognitron
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10.5120/1503-2021 |
Dharamveer Sharma and Ubeeka Jain. Article:Recognition of Isolated Handwritten Characters of Gurumukhi Script using Neocognitron. International Journal of Computer Applications 10(8):10–16, November 2010. Published By Foundation of Computer Science. BibTeX
@article{key:article,
author = {Dharamveer Sharma and Ubeeka Jain},
title = {Article:Recognition of Isolated Handwritten Characters of Gurumukhi Script using Neocognitron},
journal = {International Journal of Computer Applications},
year = {2010},
volume = {10},
number = {8},
pages = {10--16},
month = {November},
note = {Published By Foundation of Computer Science}
}
Abstract
This paper presents the development of Gurumukhi character recognition system of isolated handwritten characters by using Neocognitron at the first time. Well- known neocognitron artificial neural network is chosen for its fast processing time and its good performance for pattern recognition problems. Here we have found the recognition accuracy of both learned and unlearned images of characters. Learned images have recognition accuracy as 91.77 % and unlearned images have recognition accuracy as 93.79 %. The overall recognition accuracy for both learned and unlearned Gurmukhi characters are 92.78 %. This confirms that the proposed neocognitron artificial neural network approach is suitable for the development of isolated handwritten characters of Gurumukhi script.
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