基于图像纹理分析的交通拥堵检测算法

Traffic Congestion Detection with Image Texture Analysis

为解决目前常用的交通拥堵检测方法存在的计算量大、检测延迟大等问题,提出一种基于图像纹理分析的道路交通拥堵检测算法。该算法以图像块为基本处理单元,通过分析块内图像纹理的空域和时域变化,计算出道路的空间及时间占有率,并综合二者的变化特性实现道路交通拥堵的自动和快速检测。直接将该方法利用于现场交通场景中进行分析,避免了交通参数检测和交通建模的过程,具有计算效率高和检测延时小的优点。试验结果表明:该方法能准确、快速地检测出实际监控视频中的交通拥堵状况,满足交通管理和交通诱导系统中的实际需要。

Automatic traffic congestion detection is essential in traffic management and traffic guidance system.At present,the commonly-used traffic congestion detection method suffers from detection delay and intense computation.This paper presents an algorithm for traffic congestion detection based on image texture analysis,which analyses the change of image texture in space domain and time domain and calculates the space occupancy and time occupancy.The automatic congestion detection is achieved by synthesizing the variation of these parameters.Because the analysis is based on the traffic scene,it does not rely on traffic modeling and direct traffic parameter measurements,on which ordinary detection methods are based.Therefore,the traffic texture method performs better than common used methods in terms of detection delay and computing load.Tests are carried out to verify the performance of the method with real surveillance video.