Traffic Information Processing System And To Achieve

Intelligent Transport Systems(ITS) is the determinate approaches for the development of the modern transports,the vehicle detection and classification based on computer vision that is a important research field for the advance of the ITS。It has promising prospect in the application of the road traffic surveillance system and the highway toll system and so on. In this thesis,we research deeply the technique about vehicle detection and classification,and propose a precise and robust algorithm of detecting and classifying moving vehicles on road. The main contents can be listed as follows:This thesis designs the system of traffic information detection according to the need of traffic information detection. This thesis includes the constitutes of system hardware, image pretreatment, the achievement of parameter detection artithmetic. Secondly, the dissertation introducedmethod of video-detecting technology and principle of detecting and recognition with image-processing, such as image filtering and noise reduction,image sharpening, image enhancement, image segmentation, feature pick-up and boject recognition. On the basis of these analysis, the dissertation set up a mathematical model of background subtraction method adopted in design and realization of motor vehicle peccancy-detecting system and accomplished automatic update of background.The methods proposed in this thesis adapt to complex seenes such as large area and multiple objects, and can satisfy the requirement of vehicle detection and classification in natural environment. The research would be reasonable and valuable in the oretical and practical areas,and can be generalized to other fields of video surveillance.