摘要
针对监控环境下运动物体的检测,提出了基于Surendra背景更新的背景减除的运动目标检测方法.首先对视频图像进行灰度化并去噪,再建立一个可靠的Surendra背景更新模型,由背景消减法得到运动目标图像,最后图像进行二值化并采用形态学滤波和连通区域面积检测进行后处理,以消除噪声和背景扰动带来的影响.试验结果表明本文采用的基于Surendra背景更新算法的背景减除的方法,具有较好的实用性.
To detect the motion of objects under monitored circumstances, a motion detection algorithm based on Surendra background updating and background subtraction is proposed. The visual images are grayed and the noise is eliminated. Then a reliable model of Surendra background updating is developed. The motion information is detected by adopting background subtraction method. The images are segmented. In an attempt to minimize the negative influences of noise and background disturbance, morphologic filtering and connected region area measurement are introduced. The experimental results show that the algorithm based on Surendra is practically valuable.
出处
《南京工程学院学报（自然科学版）》
2011年第2期22-27,共6页
Journal of Nanjing Institute of Technology(Natural Science Edition)
基金
福建工程学院基金资助项目(GY-Z0566)
关键词
背景更新
背景减除
目标检测
background updating
background subtraction
motion detection
