The lane recognition and vehicle detection at night for a camera-assisted car on highway

This paper presents a computer vision system for detecting lanes and vehicles on highway at night. This system recognizes the rear-lights of vehicles from the night scene image on highway, as viewed by a camera-assisted car behind. The detection of rear-lights is usually complicated by the existence of reflector plates on ground, multiple cars, and the environment lightening. The variation of the shape/size and height of rear-lights, and the wide range of possible distance from the observing vehicle also add extra complexity to the recognition. In this research, we take the approach of first detecting the reflector plates among the bright spots in the highway night scene, which indicate the lane borders. Through the brightness and area filtering, the reflector plates can be extracted. Removing the reflector spots from the bright-spot image and using the information of detected lanes, the pairing of rear-lights to find vehicles can be simplified. Experiment shows the success of this approach in detecting multiple vehicles on highway.