Title: Recognition of the Arabic handwritten letters by the neural networks

Authors: Mohamed Senouci

Addresses: Department of Computer Science, University of Oran, Algeria

Abstract: In this paper, an Arabic character recognition system based on Artificial Neural Networks (ANN) is presented. In this system, each drawn Arabic character is represented by binary values that are used as input to a simple feature extraction system, whose output is fed to a Kohonen neural network that consists of two layers (first layer 99 neurons, second layer 28 neurons). Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the most of the other classifier method solutions, especially when the contaminating noise level is low.

Keywords: artificial neural networks; ANNs; pattern recognition; Arabic handwritten letters; Kohonen; segmentation; classification; Arabic character recognition; handwriting recognition.

DOI: 10.1504/IJRIS.2011.043546

International Journal of Reasoning-based Intelligent Systems, 2011 Vol.3 No.3/4, pp.212 - 216

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 04 Nov 2011 *

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