Arabic text recognition using neural networks
Majid M. Altuwaijri, Magdy Bayoumi · 2002
Recognizing multi-font Arabic texts is a difficult task in the area of optical character recognition (OCR) because Arabic is a cursive type language. This paper proposes a hybrid Arabic character recognition system based on Moment Invariants employing an Artificial Neural Network classifier. The feature extraction stage uses a set of moment invariants descriptors which are invariants under shift, scaling, and rotation. The actual classification is done using a multilayer perceptron network with back-propagation learning. As a preprocessing step, a new approach to segmentation of Arabic words is proposed in this paper. The system has been tested and has shown a very high accuracy.>