Dept. of Electrical Engineering, Amirkabir University of Technology, Tehran 15875-4413, Iran
Dept. of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
Car license plate recognition is addressed in this paper. Given the development of intelligent transportation systems, it is absolutely essential to implement a strong license plate recognition system. Efforts were made to put forward a novel reliable method for car license plate recognition in Iran. Each license plate recognition system comprises three main parts. The first part is the license plate detection stage. The blue color feature of the license plate margin along with Scale-Invariant Feature Transform (SIFT) algorithm were used for this purpose. The accuracy of the presented method over the database was approximately 90% in less than a second. License plate morphological features were utilized upon character segmentation. Using these features, areas with sizes close to that of the characters of a license plate may be searched. The accuracy of this method was almost 95%. A probabilistic neural network together with a Support Vector Machine (SVM) was employed at the character recognition stage. For this stage, an accuracy of nearly 97% in 55 milliseconds for each license plate was achieved.