Stereo vision based on-road vehicle detection under illumination changing conditions using self quotient image

Today the many of automotive research groups study how to reduce vehicle accidents. For this reason, they have been developing the advanced driver assistance system (ADAS). In ADAS, the various sensors are used for recognizing the driving situations. For example, there are supersonic wave sensors and radar sensors and so on. In particular, in computer vision research groups, the vision sensors (ex. CCD, IR) are used for this. But it has some difficult problems because the vehicles are mainly driven in outdoors. The images captured by outdoors have various illumination conditions due to weather. It makes difficulty to detecting vehicles in images. In this paper, we introduce the vehicle detection method when the input images of system have illumination changes. We use the self quotient image (SQI) algorithm for illumination equalization. But SQI algorithm produces many false positive results. So we eliminate the false-positive results using stereo vision technique. In main section, we explain this method in detail. And we prove the proposed method has superior performance than existing systems using experiments.