摘要
针对现有智能交通系统对道路多样性事件识别功能不足的问题,设计了一套基于计算机分布式视觉模型的车辆监控系统;监控系统设计了底层控制站视觉信息采集模块和DP总线信息传递模块,准确、实时地检测出拥堵、行人、停车等交通多样性事件,增加了系统功能;由DSP中央处理模块组成的,利用前100帧道路图像的均值作为初始背景,根据不同交通事件获取背景图像进行实时更新,利用差分法获取差分图像,并进行形态学处理;根据DSP处理器得到的二值图上运动目标的特征,判断发生了哪类交通事件;针对该系统的实验结果表明,系统对车祸、拥堵、等事件检测正确率达到86.5%,对正常车流检测识别正确率达到86.9%,适用于信息融合型的交通智能系统应用。
Design a set of computer based distributed visual model vehicle monitoring system. Design on the bottom control station visual information acquisition module and DP bus information transfer module accurately and real time detection of congestion, pedestrians, park ing and traffic incident happened. The central processing module of DSP. With the former 100 frame the mean as the initial background; Ac cording to the different traffic event for background image real time updateUsing finite difference method for difference image and mor phology processing According to the DSP processor get binary chart moving target characteristics, judge what kind of traffic incident hap pened. According to the system of the experimental results show that the system of car accidents, congestion, and incident detection accuracy can reach 86.5 %, the normal traffic flow detection identification accuracy can reach 86.9 %, suitable for information fusion type traffic intel ligent system application.
出处
《计算机测量与控制》
北大核心
2013年第11期2991-2993,共3页
Computer Measurement &Control
关键词
交通事件检测
背景差
实时检测
traffic incident detection
background difference
real-- time detection