Recognition Technology Based On Image Processing Technology And Nbclassifier Models

Intelligent Transport Systems (ITS) is the determinate trend for the development of the modern transports, the vehicle automatic classification based on video technology is an 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. The technique about vehicle automatic classification system is researched deeply. The main research work of this paper presented as follows:(1) Traffic video Image preprocessing. By analyzing several common images filtering, the preprocessing of traffic scene images by using median filtering are proposed.(2) This paper proposes a new fast range scanning method to pick up the characteristic of the moving vehicle. The basic principle is that in the AOI area all the lengths of all the detected targets are gained through line scan and regard the largest width as the width of the vehicle. Scan in the gained width area until all the pixels are white on a line, then the length of the vehicle can be obtained. The result shows that the algorithm can also obtain precise characteristic values.(3) This paper puts NBClassifier theory into traffic vehicle automatic classification system. Use the actual vehicle characteristic data of length and width as training samples to train NBClassifier off online. The standard vehicle images are captured from CCD camera, with the vehicle characteristic data of length and width obtained by using edge detecting algorithm as tested samples. Then the vehicle type can be judged by means of the trained NBClassifier according to the method proposed in this paper. Experiments show that it has a higher accuracy by compared with BP network in the same test.