The Research On Vehicle License Plate Location And Segmentation Of License Plate Recognition System

With the high-speed development of our national economy, there are more and more construct in the domestic expressway, urban road, and parking area, etc. The requisition on the traffic control, safety management improves day by day. The intelligent traffic system (ITS) has already become the main direction of present traffic administration development, and vehicle license plate recognition (LPR) system as core of ITS, plays a very important role. It occupies important role in the project management of expressway, urban road and parking area, etc. Its wide application will contribute to the process of the traffic management automation of our country.Being a special computer vision system in the real-time case, the LPR system mainly includes the subsystem of license plate detection and character recognition. The LPR system involves numerous discipline domains, such as Pattern Recognition and Artificial Intelligence, Computer Vision, Digital Image Processing etc. The detection of license plates is the key of LPR system. Because of the complex of image background, the uncertainty of plate position and image quality, the location of plates is not satisfied. Therefore, the study on the algorithm of license plate location is always the hotspot problem.In this paper we have summarized the latest research achievements and development of license plate location and segmentation and discussed the intrinsic characteristic of license plate. On the basis of previous work, firstly, we studied the texture characteristic of license plate and put forward our algorithm based on texture analysis. We define two parameters to describe it. Mathematical morphology is the new technology of image processing. In order to exactly locate the licenses, we make use of series of morphological transformation. We also employ other prophetic knowledge such as the ratio of width and length, etc. The experimental results show that this algorithm is efficient in locating the licenses while not sensitive to unconstrained illumination conditions and irregular background. Otherwise we do research for character segmentation. By means of projection-based character segmentation algorithm, we obtain some preferable results that provide the foundation for character recognition.This paper presents the method of us in details. At the end of the article, we introduce the prospect of the following work.