A traffic-congestion detection method for bad weather based on traffic video

Abstract

In order to solve the problem that the result of traffic congestion detection in bad weather is inaccurate, we analyzed current vehicle identification algorithms and image processing algorithms. After that, we proposed a detection method of traffic congestion based on histogram equalization and discrete-frame difference. Firstly, this method uses discrete-frame difference algorithm to extract the images that have vehicle information. Secondly, this method uses the histogram equalization algorithm to eliminate the noise of the images. Finally, this method recognizes the vehicle from the video and computes the traffic congestion index by the calculation method based on discrete-frame difference. It has proved by experiments and theoretical analysis that this method decreases false-negative rate and increases the accuracy rate of automatic traffic congestion detection in bad weather.