Abstract—Automatic License Plate (LP) recognition uses optical character recognition to read LPs on vehicles, such system is essential for traffic control, theft control, electronic toll collection, parking lots access and/or billing. The proposed Arabic LP recognition system is applied to Saudi Arabian LPs which have two different formats. Therefore, this system recognizes both Arabic and Indian numerals as well as limited Arabic and Latin alphabets. The system goes through many preprocessing steps in order to produce segmented characters of the LPs images. The feature extraction step uses the count of black pixels from the horizontal projection profiles in addition to the black pixel distributions in divided zones of the character image. The recognition is performed separately based on different regions; therefore, applying the recognition process to specific regions of the LPs; speeds up the processing due to the limited number of comparisons. The recognition step uses both a distance classifier and Neural Network (NN) classifier to discriminate between the different characters. This proposed system provides more importance to the preprocessing stage whose success guarantees the successful performance of the whole system. Also, the Arabic characters are verified against the corresponding Latin characters and similarly the Arabic numerals to their corresponding Indian numerals. The system is tested on 462 correctly localized LPs providing a 98.63% character recognition rate and a total of 94.9% accepted LPs.

Index Terms—Arabic license plate, recognition, projection profile, feature extraction, Mahalanobis distance, Neural Networks (NNs).

Yasser M. Alginahi is with Department of Computer Science College of Computer Science and Engineering, Taibah University, P.O. Box 344,Postal Code: 41411, Madinah, Saudi Arabia (email:yginahi@taibahu.edu.sa, alginahi@gmail.com).

Cite: Yasser M. Alginahi, " Automatic Arabic License Plate Recognition," International Journal of Computer and Electrical Engineering vol. 3, no. 3, pp. 454-460, 2011.