The Crux Of Intelligent In-cars Pre-warning System Based On The Infrared Vision

With the development of traffic in the modern society, increasing busyness of traffic conditions has become the most direct safety problems, and various types of accidents increased. As a hard-core of the Intelligent Transportation System, the in-cars pre-warning system is very hot in the research field of vehicle engineering in today's world.Through analyzing the domestic and international research of the in-cars pre-warning system, we found that these vision systems doesn't work well in rain, fog and other adverse weather conditions. So in this paper we designed the in-cars pre-warning system which based on the infrared vision detection.Firstly, active infrared image collection system was designed after analysis the performance of several infrared image collection systems. It mainly makes up of infrared LED light, low-luminance CCD camera and infrared filter. Secondly, based on the characters of the infrared road images and the priori knowledge, isosceles trapezoid was used to segment the image. Then we studied the pre-processing method of infrared images which contains median filtering, Sobel edge detection and the largest minimum variance threshold segmentation. Next, the area of interest (AOI) was determined after detect the edge of lane line by Hough transformation. The system use the principle of gray change to search the front cars in the area of interest, use Kalman filtering to track front cars. Finally, based on the geometric model projection, flat road hypothesis is used to set up the coordinate transformation equations between the world coordinate system, camera coordinate system, image coordinate system and frame buffer coordinates, then derived the formula for measure distance from two cars and the safe distance criterion.After the process above, this system can detect the front cars and site them quickly and accurately, implement the in-cars pre-warning system function.