Research On Vehicle License Plate Location Based On Computer Vision

The thesis is a part of the research on the LARS(License Plate Automatic Recognition System). LARS is the important application of computer vision and pattern recognition in the intelligent transportation system, and it is an important part in the ITS.License Plate Location is the key technique to License Plate Recognition. Finding the accurate location of the license plate is the premise of LRP, and is the key of improving the system identification rate. In this paper, two aspects about LPL are described as follow:1. A new license plate location method, which is based on color segmentation, license plate shape analysis and gray-scale morphology, is introduced. Firstly, the color image in RGB color format is converted to HSV color format. According to three element value ranges of the licenses plate color in HSV color space, a five_scale gray image is constructed to filtrate the plate images background. Secondly, mathematical morphology is used for processing the continuous areas that are fulfilled by color segmentation so that their holes are filled and their noises are erased. At last, according to the geometrical and texture features, continuous areas' shape analysis is applied to the continuous areas to eliminate the false regions so that the goal plate is located correctly. The main characteristic of the new method is that color features and morphologic features of the plate are combined.2. Based on the Visual C++ integrated developing environment, the program is designed by the stepwise refining method. The experimental result shows that this system can quickly, accurately find the location of license plate, and the algorithm has better interference immunity.