Research On License Plate Location Algorithm Of License Plate Recognition System

With the development of information technology and intelligence technology, the informatization and intelligentizing of traffic management is the trend. License Plate Recognition system (LPR) is the core of Intelligent Traffic System (ITS). It is very important in modern traffic management systems. In recent years, the study on the critical techniques for LPR has already become an important research field of scientific circles. In this paper we discuss the three parts of License Plate Recognition Systems: image pre-process, license plate location and character segmentation, and make a deep research on some important and key technology.A hybrid license plate location scheme is presented in this paper, which is mainly implemented as following several stages. At first, in the license plate roughly location stage, according to the continuity of transverse integral projection of the license plate region, and according to the number of white change points taking up a majority of the license plate, we use a rectangle to traverse the whole marginal-binary-image of the plate rage. After extracting the approximate license plate, judgment of the base color of the license plate is done, because the information of color is conserved when we do pre-treatment of the images. Second stage is accurately extracting the license plate. We use a method including horizontal and vertical operators to locate the license plate region; the pixel-rate is utilized to verify the real license plates which are the pixel of the plate color compare to the pixel of the candidate license plate color. In the last section, the slant correction of license plate is necessary to use the method combined with Hough transform and projection, so that the correspond plate region is present. Then we excise the border of the characters and segment them.Based on the experiments dealing with images taken under various real world conditions, the results prove that this proposed method can relatively locate license plate and segment characters. It shows that the performance of the system is promising, robust and timely.