关键词: 均质雾天, 图像拐点, 能见度估计, 车道线检测

Abstract: The traditional visibility meters are expensive, their sampling is limited, and some of the existing video measurement methods need artificial markers and are of poor stability. In order to solve these problems, a new algorithm for weather recognition and traffic visibility estimation through fixed camera was proposed based on lane detection and image inflection. Different from previous research, our traffic model added homogenous fog factor in traffic scenes. The algorithm consisted of three steps. Firstly, calculate the scene activity map. With the help of the Area Search Algorithm (ASA) combined with texture features, extract area for identifying. The current weather condition is foggy if the pixels from top to bottom in the extracted area change in hyperbolic fashion. At the same time calculate inflection point of image brightness curve in the extracted area. Secondly, detect traffic lane based on the retractable window algorithm, extract the lane’s endpoint and calibrate the fixed camera. Finally, according to the visibility definition, calculate traffic scene visibility by International Meteological Organization based on monocular camera model and light propagation model in fog weather condition. Through experiments of visibility estimation for three different scenes, the experimental results show that the algorithm is consistent with human eye’s observation and the accuracy rate is up to 86% while the inspection error is within 20m.