Title :
Offline Arabic text recognition system
Author :
Sarfraz, Muhammad ; Nawaz, Syed Nazim ; Al-Khuraidly, Abdulaziz
Author_Institution :
Dept. of Inf. & Comput. Sci., King Fahd Univ. of Pet. & Minerals, Dhahran, Saudi Arabia
Abstract :
Optical character recognition (OCR) systems provide human-machine interaction and are widely used in many applications. Much research has already been done on the recognition of Latin, Chinese and Japanese characters. Against this background, it has been experienced that only few papers have specifically addressed to the problem of Arabic text recognition and languages using Arabic script like Urdu and Parsi. This is due to the lack of interest in this field and in part due to the complex nature of the Arabic language. This paper presents a technique for the automatic recognition of Arabic printed text using artificial neural networks. The main features of the system are preprocessing of the text, segmentation of the text to individual characters, feature extraction using moment invariant technique and recognition using RBF network.
Keywords :
feature extraction; image segmentation; natural languages; optical character recognition; radial basis function networks; text analysis; Arabic language; Arabic script; Arabic text recognition; OCR; Parsi; Urdu; artificial neural network; feature extraction; human-machine interaction; optical character recognition; radial basis function networks; text preprocessing; text segmentation; Application software; Artificial neural networks; Character recognition; Computer science; Man machine systems; Minerals; Natural languages; Optical character recognition software; Petroleum; Text recognition;
Conference_Titel :
Geometric Modeling and Graphics, 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7695-1985-7
DOI :
10.1109/GMAG.2003.1219662