TY - JFULL AU - Z. Shaaban PY - 2008/6/ TI - A New Recognition Scheme for Machine- Printed Arabic Texts based on Neural Networks T2 - International Journal of Computer and Information Engineering SP - 1457 EP - 1461 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/3912 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 17, 2008 N2 - This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate. ER -