Persian on-line handwritten character recognition by RCE spatio-temporal neural network

Authors:
Mehdi Moghadam Fard;Maryam Moghadam Fard;Behrouz Minaei Bidgoli;Masroor Hussain
Affiliations:
Iran University of Science and Technology, Tehran, Iran;Iran University of Science and Technology, Tehran, Iran;Iran University of Science and Technology, Tehran, Iran;Ghulam Ishaq Khan Institute, Topi, Pakistan
Venue:
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Year:
2008

Citing 5
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Abstract

In this paper a new Persian on-line handwritten character recognition system using neural network is presented. The proposed system is based-on a newly developed Spatio-Temporal Artificial Neuron (STAN) which is well adapted for the recognition of Spatio-Temporal patterns. In this model the strokes of a character generated by a digitizing tablet is presented in form of a sequence of spikes corresponding to displacement of the stylus. The architecture of the proposed system is based on three modules preprocessing, spike extraction and classification. The second and third modules are based on neural architectures which have STANs as their neurons. Our database comprises the handwritings of 80 persons. Each person has written 10 times each of 32 characters