Improved DBSCAN clustering algorithm based vehicle detection using a vehicle-mounted laser scanner

Combining with the practical application of driving environment, this paper proposed a vehicle detection method based on improved DBSCAN clustering algorithm using a laser scanner. First, the vehicle and sensor coordinate conversion model was built to fuse the data from the laser scanner and the camera. Then the DBSCAN algorithm was improved to cluster the laser scanner data points and remove the noises at the same time. Based on the models of vehicle shape features, the preceding vehicles could be detected using shape matching. Finally, the result of the detection was projected onto the video image. The tests on running vehicle show that the proposed method can detect the vehicles efficiently in real traffic environment.