A Fast Approach of Road Congestion Detection Based on Image Processing
LI Wei
Abstract：This paper proposes a fast detection algorithm for urban road traffic congestion based on image processing technology. Firstly, to speed up the processing and freely select a vehicle area, it puts forward a vehicle area detection with human-computer interaction. Then, by using the difference of texture features between congestion image and unobstructed image, it presents the vehicle density estimation based on the texture analysis. Through the image grayscale relegation, gray level co-occurrence matrix calculation and feature extraction, the energy and entropy features that can reflect vehicle density are obtained from the vehicle area. After the feature training, the decision threshold could be obtained and traffic congestion could be carried out. Experimental results show that the accuracy of algorithm is as high as 99%, and the processing speed could satisfy the real-time requirement in engineering.
Keywords：traffic congestiontraffic video monitoringtexture analysisvehicle density detection
Publication Date：2015-01-01
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：6( 11-16 )