Application Research Of Image Processing Technology In Traffic Violation Identification

With the improvement of people’s living standards,family cars have gradually become popular,and the increase in car ownership has brought great convenience to people’s lives.At the same time,traffic congestion,traffic violations and traffic accidents have increased.In order to be able to control urban traffic more scientifically and rationally,intelligently monitor the status quo of urban traffic operations,and automatically identify vehicle information and vehicle violation information,the government began to strengthen the construction of intelligent transportation systems.The intelligent transportation system can intelligently identify the traffic flow information,vehicle information and vehicle violation information on the road,and analyze the vehicle traffic and road congestion of the road information through the analysis of the vehicle information on the road,and pass the road information through the information release system.The release system is released,intelligently regulating traffic and reducing urban congestion.How to obtain road traffic conditions and vehicle information is part of intelligent transportation research.This research mainly uses image processing technology to obtain vehicle license plate information and vehicle violation information.The traditional video surveillance facility uses a video camera to obtain road video surveillance information,and then uses the industrial computer to process the video information to obtain road information.This combination method has seriously hindered the construction of intelligent transportation system terminal equipment because of the high cost.This study uses a Samsung Exynos 4412 processor as the main hardware platform,equipped with a Linux operating system,ported the Open Source Computer Vision Library(OPENCV)for image processing operations,and uses a webcam for traffic video.Extraction of information.The way to use this hardware combination is to reduce hardware costs and save on intelligent transportation system construction costs.One direction of this research is to extract the vehicle’s violation information.In this study,edge detection is used to detect the lane line,the background difference method is used to detect the side of the moving vehicle,and the HSV color space method is used to identify the traffic light in the designated area.Combined with the information extracted by the image processing,it is possible to detect whether the vehicle has a violation information.The vehicle violation information is detected,and the system automatically binds the license plate number of the illegal vehicle to achieve the purpose of automatically identifying the vehicle violation information.It is also a direction of this research to extract vehicle license plate information through image processing technology.The license plate information is extracted to reduce the pressure of manual vehicle information extraction and improve the efficiency of work.In this study,the license plate information is extracted,and the HAAR feature classifier of HAAR feature training is used to locate the license plate area.At the same time,the traditional Sobel edge detection method is used to locate the license plate.After the license plate area is located,the support vector machine(SVM)is used to determine the real license plate area.After the license plate area is determined,the corresponding image processing technology is used to extract the character area,and then the BP neural network is used to identify the character of the Chinese character and the alphanumeric character respectively,and finally the license plate information of the vehicle is output.The program based on the Linux operating system equipped with the OPENCV image processing library is transplanted to the embedded system with the Samsung Exynos 4412 as the core processor to verify the above vehicle violation identification and vehicle license plate number extraction algorithm.It has been verified that the system can effectively locate and identify the vehicle’s violation information,and can also effectively identify the vehicle’s license plate information.