A Deep Learning Approach to Recognize Mixed Fonts Printed Arabic Characters

Abstract

There is an immense need for recognition systems that rely on Arabic characters to provide a reliable and fast processing of data. Since Arabic writing is widely used in various real-world applications, this motivated us to develop a recognition system which recognizes mixed fonts printed Arabic letters of different sizes besides ligatures, digits, and punctuation marks. The proposed system consists of the preprocessing phase, the feature extraction phase, and the recognition phase which exploiting two models of Convolutional Neural Networks CNNs to recognize the characters. The experimental results are very promising as the second model (CNN model 2) outperforms the first model (CNN model1) and achieves an accuracy rate of 99.86%.