分块帧差和背景差相融合的运动目标检测

提出了一种分块帧差和背景差相融合的运动目标检测方法。该方法利用图像分块建立初始背景模型,将视频图像划分为多个子块,对帧间差分图像的各子块进行自适应阈值检测,完成运动目标的粗分割,采用双阈值背景差分和邻域背景差分法对粗分割出来的运动区域进行细分割。背景采用自适应更新方法,能够克服光照变化和背景干扰。实验结果表明,该方法运算速度快、鲁棒性好,能够准确检测出运动目标。

Moving object detection based on consecutive blocks frame difference and background subtraction

This paper proposed a novel approach for moving detection, which employed blocks frame difference and background subtraction. It used block processing method to establish the initial background model and it divided the sequence ima-ge of video into several blocks which was detected by self-adaptive threshold inter-frame difference, and separeted roughly the motion region. Then it carried on fine-grained segmentation through double-threshold background subtracting for the motion region, and used the adaptive background updating to overcome the light changing and background interference. Experimental results indicate that the method has the characteristics of fast operation and great robustness, and it can detect the moving object effectively.