Video Fog Detection Based on Dynamic Texture Analysis

Abstract

The accurate recognition of outdoor weather has a very important application value in weather prediction, disaster warning, automatic driving and other fields. Fog, rain, snow and other bad weather pose a serious threat to driving safety, which is the focus of outdoor weather recognition. At present, video surveillance system has been widely used in highway surveillance system, and fog detection based on video image has received extensive attention. This paper will study fog detection technology based on dynamic texture features.This paper uses MATLAB as the simulation platform to realize the fog detection based on optical flow method. First of all, considering that the fog area in the video image will change in shape and concentration over time, appropriate anti-interference methods including median filtering are selected to complete the preprocessing; Secondly, according to the characteristics of fog, such as diffusion, the method of feature calculation and motion analysis based on optical flow is studied; Finally, the corresponding motion rules and analysis methods are established to detect and recognize the foggy video regions. The smoke video is processed in this paper, and the results show that the fog area can be accurately detected and the detection effect is good. The experimental results show that the processing method in this paper has a good effect, and has a high application value in video fog detection.