Research Of Road Detection And Tracking System Based On Machine Vision

Intelligent navigation system based on machine Vision is a part of the intelligent transportation systems. It is the key technique of intelligent vehicle guidance. The road image tracking system plays an important role in the intelligent navigation system. This paper researches the algorithm of lane detection and track for the visual intelligent vehicle navigation system based image processing and analysis.In this paper, research background, meaning, current status of internal and world, trend and difficulties of the intelligent transportation systems is firstly introduced.Then Machine Vision theory and method for the realization of the road detection are introduced. In this paper, the visual sensor (camera) is used to collect the road images, and Virtual C + + is used for the simulation algorithm.In image filtering and enhancement, comparing with the result of the trials, especially comparing the images after adding noise to simulate the real climatic condition, it can be found that the effect of median filtering is fast, good to use, and the edge is clearer then others. It is in favor of the future to deal with. In image edge, by simulate experiments, the paper uses Sobel edge detector. It is simple. Its operation speed is quick and processes lubricity and series. And it affects by the noise smaller. It is suitable for detection of the road image tracking system. For the real time and robustness of system, the road image must be binary. By the improvement of optical threshold segment, iteration mean is used for the advancement of resist noise. For the distilling road line better, Mathematical Morphology based on assemble is used for the sealing and filtering of road. Abort the line images, as the restriction condition of the line and so on. Hough transform is used of distilling the line. The real time and robustness of Hough transform is very good. And it links the short ling of one line. By the parameter of road line, the deviation of site and angle are known between the road line and vehicle. And Kalman filter is used for tracking the road line.In this paper, it also proposes that using GPS, infrared and other heterogeneous multi-sensor information fusion at the same time for different road. The advantage of using different kinds of multiple sensors is that can improve the effectiveness of navigation systems.The algorithm proposed by the paper are used to process actual lane image, simulated results show that the algorithm is right and effective. There are 48 figures and 34 references in this article.