Author(s): Akram AL-Hadad, Hazem Elbakry, Reham R. Mostafa
License plate localization is considered the cornerstone for any license plate recognition system. Its reliability and performance have a majore influnece on the whole license plate recognition syste m. In this paper, a new technique for license plate detection is presented. The first step is detecting the vertical edge using Sobel mask, and then the horizontal projection is applied to filter the edge image regions. Morphological operations and connected components labelling are used to get the candidate regions. Finally, support vector machine is used to examine the candidate regions and determine the license plate. Dataset downloaded from the internet is used to train SVM and test the proposed technique. This dataset contains 514 images of cars and vans. The images are captured in various illumination conditions, raining days, taken from different angle. Furthermore many of them have very complex background, shadow. In addition, many regions are similar to the plate region. Simulation results of the proposed technique show accuracy of 92.2%. Keywords: Pattern recognition, computer vision, image processing, license plate detection, SVM, morphology operations.