Saudi Arabian License Plate Recognition System Muhammad Sarfraz, Mohammed Jameel Ahmed, and Syed A. Ghazi Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran – 31261, Saudi Arabia. {sarfraz, jameel21, aghazi}@ ccse.kfupm.edu.sa Abstract A License Plate Recognition (LPR) System is one kind of Intelligent Transport systems and is of considerable interest because of its potential applications to areas such as highway electronic toll collection, Traffic Monitoring System and so on. This paper proposes an automatic license plate recognition system for Saudi Arabian license plates. The system captures the images of the vehicles with a digital camera. An algorithm for the extraction of license plate has been designed and an algorithm for segmentation of characters is proposed. The performance of the system has been investigated on real images of about 610 vehicles captured under various illumination conditions. Recognition of about 95% shows that the system is quite effective. 1. Introduction Vehicle license plate recognition is one form of automatic vehicle identification system. Real time LPR plays a major role in automatic monitoring of traffic rules and maintaining law enforcement on public roads. This area is challenging because it requires an integration of many computer vision problem solvers, which include object detection and character recognition [5]. The automatic identification of vehicles by the contents of their license plates is important in private transport applications. There are many applications of such recognition systems, some of them are border crossing control, automatic parking attendant, speed limit enforcement, security, and customer identification enabling personalized services [1]. There are multiple commercial license plate recognition systems available in the current literature [12]. Applications such as SeeCar, Perceptics, and Pearpoint are commercially available and some of the research projects include Esprit 5184 Locomotive [10], software architecture thru DLL’s [1]. The steps involved in recognition of a license plate are Image acquisition, License plate extraction, Segmentation, and Recognition. Image acquisition is the first step in an LPR system. The current literature discusses different image acquisition methods. Naito et. al. [8] developed a sensing system, which uses two CCDs (Charge Coupled Devices) and a prism to split an incident ray into two lights with different intensities. Salgado et. al. [10] used a sensor subsystem having a high resolution CCD camera supplemented with a number of new digital operation capabilities. The proposed system uses a high resolution digital camera for image acquisition. License plate extraction is the key step in a LPR system, which influences the accuracy of the system significantly. Different approaches for the extraction of the license plate depending upon the back ground color of the image are presented in [13]. Hontani et. al. [4] proposed a method for extracting characters without prior knowledge of their position and size in the image. Kim et. al. [5] used two neural network-based filters and a post processor to combine two filtered images in order to locate the license plates. Park et. al. [9] devised a method to extract Korean license plate depending on the color of the plate. The proposed approach uses matching of vertical edges. This approach involves three steps, vertical edge detection, filtering and vertical edge matching. In the Segmentation phase, individual characters are isolated from the license plate. Various approaches have been proposed in the literature. Nieuwoudt et. al. [7] used region growing for segmentation of characters. Morel et. al. [6] used partial differential equations (PDE) based technique for image segmentation. The proposed approach for segmentation is based on vertical projections on the extracted license plate and then counting the number of black pixels in each column. Proceedings of the 2003 International Conference on Geometric Modeling and Graphics (GMAG’03) 0-7695-1985-7/03 $17.00 © 2003 IEEE