Digital Signal Processing


Zernike Moments and Neural Networks for Recognition of Isolated Arabic Characters

Authors: Mustapha Oujaoura, Rachid El Ayachi, Mohamed Fakir, Belaid Bouikhalene, Brahim Minaoui

The aim of this work is to present a system for recognizing isolated Arabic printed characters. This system goes through several stages: preprocessing, feature extraction and classification. Zernike moments, invariant moments and Walsh transformation are used to calculate the features. The classification is based on multilayer neural networks. A recognition rate of 98% is achieved by using Zernike moments.

Comments: 9 Pages.

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[v1] 2012-08-18 21:57:25

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