Highway Visibility Detection Method Based on Surveillance Video

Abstract

Low visibility weather has seriously affected daily traffic management and safety of life and property. Aiming at the problem that highway in low visibility environment is prone to traffic accidents, a highway visibility detection method based on video surveillance is proposed, and the surveillance video data of each section are analyzed. Based on the traditional dark channel prior, the highway visibility detection method converted the surveillance video frame into gray image, and extracted the air transmittance and atmospheric light value contained in the surveillance image by combining the adaptive guided filtering algorithm and quadtree image segmentation algorithm. Then based on the visibility calculation model, the visibility distance of the road was estimated according to the actual distance and offset angle between the monitoring equipment and the detection object. The experimental results show that the optimized image processing method can solve the problems of low image clarity, color distortion, and poor scene adaptability. The detection of visibility error rate meets the accuracy requirements of highway visibility detection in China. Finally, a road real-time visibility detection and warning system is applied based on the corresponding early warning strategies of each visibility level.