A Study of Automatic License Plate Recognition Algorithms and Techniques

One of the most useful techniques in traffic management, speed control and security improvement in big cities is Automatic License Plate Recognition (ALPR). During the last two decades many techniques for license plate detection have been developed. Four methods suggested for vehicle license plate recognition are studied and compared in this paper. The main focus of all of these methods is on suggesting a robust, and at the same time simple solution to resolve the common issues in license plate recognition. The main issues taken in to consideration include sensitivity of these systems against environmental and geometric changes. The first method is based on creating a cascade classifier using statistical features. The second method uses a combination of Hough transform and Contour algorithm in a boundary line approach. The third method makes benefit of mean shift approach in the spatial-range in order to create candidate regions, and Mahalanobis classification for character identification, and the fourth system uses morphological operations to decrease the number of candidate regions.