Application Of Digital Image Processing In Vehicle License Plate Recognition System

In 21 century, with the fantastic spur in economy and rapid development of the owning amount of vehicles, the highway communication becomes more and more deteriorative, which brings lots of pressures to the environment and the society. Intelligent Transportation System is a system which can process the transportation management efficiently on the basis of comparative perfect road infrastructure, combines technetronic,information technology,sensor technology and system engineering technology. It can solve most of the problems, that's why many scientists pay attention on it.License Plate Recognition (LPR) is one of the critical techniques for ITS. The system can register, verify, monitor the vehicle or report to police with automatic license plate recognition automatically. So it can be used in many kinds of occasions, such as the charges system of expressway, monitoring system at road and roll-gate, changes and monitoring system at the district, parking area, guide system, the system counting the quantity if vehicle passing in a certain period time, etc.This paper accomplished research and design of vehicle LPR algorithm. The system consists of three main modules:(1) Location of vehicle license plate. First it introduces a method which uses morphology to extract the plate, then, it presents another method to extract the plate which uses projection analysis. (2) Character segmentation. It divided the LP image to independent character and the method it adopted uses projection feature and the character's tincture. (3) Character recognition. It puts emphasis on the non-Chinese characters using character statistics.Based on the experimental results, it proves that this proposed method can relatively locate license plate,segment characters and recognize them, the performance of the system is promising. It indicates that combine feature extractions and the other methods to artificial intelligence under the principle of efficiency and practicality will be major development tendencies of pattern recognition in the future.