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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have