Road Recognition Based On Infrared Images And Road Tracking

Intelligent Vehicle (IV) System is a new field in which many countries research pay attention to in recent few years. The vision system in it needs real-time checking the environment and confirming the boundary of the road, so that the intelligent vehicle rides automatically, steadily and safely without manual operation. Using infrared camera to acquire images is a common method of the vision system. So road recognition of infrared image becomes a research emphasis of Intelligent Vehicle System.The paper primarily explicates some algorithms about infrared image processing and that how to recognize roads effectively. The paper researches some algorithms in three ways. Firstly, in image pretreatment. The paper respectively discusses some methods of image processing about gray level stretch, image smoothness and image sharpness from point domain and neighborhood domain. Secondly, in threshold analysis, the paper gives the methods of histogram pretreatment and automatic threshold selection based on histogram and gray level statistic. Finally, in edge detection, the paper gives some traditional methods of edge detection, at the same time, it propose a new method based on string-edge detection.The paper cites "generalized-Hough transform" to perform curve fitting, that is, draw out the edge of the road, as well as possible corresponding to different road model, such as "beeline model" and "parabola model". Because of the complexity of roads, the paper makes certain hypothesis and deduction on the roads, and integrates the knowledge into kinds of algorithms, so that some results of road recognition have a good effect.