Vision-based vehicle detection in the nighttime

In this paper, we present a vision-based vehicle detection method for collision warning of driver assistance system on highway in the nighttime. The major function of our work is to find preceding vehicles in the dynamic background. The system captures the image of road environment by a camera mounted on the windshield of the test car and uses multi-level image processing algorithms to extract taillights of preceding vehicles and identify the proceeding vehicles by taillight clustering processing. At the same time, it estimates the related distance between the test car and the preceding vehicle for collision warning. In our experiments, the system is implemented on an embedded system with Linux operation system, open source codes and limited hardware resources. With the results of our experiments, it shows that the system can correctly verify the proceeding vehicles in the nighttime under the real-time requirement.