Study On Recognition Algorithm Of Vehicle License Plate

With the fantastic spur in economy and rapid development of the owning amount of automobile, the highway communication becomes one of the most important communications and transportation ways in our country. And now it is infrastructures that the country developed energetically. Also crowded urban traffic needs more advanced and more effective traffic administration and control system. So Intelligent Transportation Systems(ITS) which makes use of electronic information technology to raise management efficiency,traffic efficiency and traffic security becomes main direction of traffic administration. License Plate Recognition (LPS) is one of the critical techniques for the intelligent transportation system. The system can automatically register,verify, monitor vehicle or report to the police with automatic recognition for vehicle license plates. So it can be used in many kinds of occasions, such as the charges system of expressway,monitoring system at road and roll-gate,charge and monitoring system at the district,parking area,guide system,the system counting the quantity of vehicle passing in a certain period time, etc.. Neural net pattern recognition is one of the important research directions in the field of pattern recognition lately. It has advantages of stronger ability of self-organization learning, revising, robust and non-linearity-handling, So neural net pattern recognition is widely used on all kinds of fields compared with traditional pattern recognition. And character recognition of vehicles' license plates is the important application of computer vision and pattern recognition in the intelligent transportation management and detection,the improved accuracy of vehicles' license plates character recognition system is required. Combining them is taken as the start of this article.In the article, neural pattern recognition is considered as the recognition method and vehicles' license plates is taken as recognition object,which is to improve the recognition rate of the character recognition of vehicles' license plates under noising circumstance.Based on image procession technology and character recognition, computer vision technology and artificial neural network technology, the paper deeply researches and analyses an automobile license plate identification system. Chapter 1 gives a full introduction of the present situation of technologies in automatic number-plate recognition all around the world. It analyzes that the development tendency of technologies of automatic number-plate recognition on the basis of discussing the specialization of automatic number-plate recognition in our country. In chapter 2, there are some brief introduces of pattern recognition and design of an automobile license plate identification system. Chapter 3 discusses some basic principles of image pretreatments and feature extraction. Chapter 4 analyzes the structure of the neural network with relevant theories and emphatically discusses the theory principle of the neural network and the application method in character recognition with it. Based on the theories of the first two chapters, chapter 5 introduces the theoretical foundation and method of the design of the license plate recognition system in detail. In this system, character feature of rough grid and direction-line is extracted. Lastly neural network is used as a method to recognize the single character. As the test result, it proves that this recognition method can relatively recognize characters and system's performance is good. It shows that combined feature extractions and recognition techniques can improve the ability of recognition, and the combination of neural network and artificial intelligence under the principle of efficiency and practicality will be two major development tendencies of pattern recognition.