Arabic Character Recognition Using Neural Networks

This paper proposes a technique for recognizing Arabic characters. This technique involves of three parts: body classifier, complementary classifier, and aggregate classifier. The body classifier is designed to recognize the main body of the unknown character. It uses a Hopfield network to enhance the unknown character and to get rid of noise and associated complementary. Furthermore, it uses a backpropagation network to recognize the main body of the enhanced unknown character. The complementary classifier is responsible of recognizing the number of dots or zigzag that are associated with the body of character and their position. The aggregate classifier combines the results of the previous two classifiers and classifies the whole unknown character. The proposed technique has been implemented shown a reasonable recognition rate. Key-Words: Neural Networks, Backpropagation Network, Hopfield Network, OCR, Character Recognition, Arabic Character Recognition, Pattern Recognition.