基于改进混合高斯模型的运动目标检测方法

摘要

针对传统高斯模型易将背景显露区域检测为前景问题与对复杂场景下噪音处理效果差的缺陷,提出了一种混合了三帧差算法的改进混合高斯模型算法.利用三帧差算法快速确定背景显露区域与前景的优势,提高了算法对背景显露区域的适应性;提出一种背景模式邻域更新法,提高了对复杂背景噪音的抗干扰性.通过实验证明,该算法与传统方法相比,在复杂背景下减少了大量噪音,学习周期短,提高了对天气、摄像头震动等干扰的抗性,优化了背景显露引起的"影子"噪音问题.%For the traditional Gaussian mixture model, it is prone to detect the background as the foreground region and has poor effect in complex background, so this paper puts forward an improved algorithm combined with three frame difference method. First, we use the three frame difference method to improve adaptation of the revealed background region. Second, we use the means of background neighborhoods update to improve the resistance to complex background noise. The experiments prove that compared with the traditional method, the improved algorithm reduces large amount of noise and shortens learning cycle, and improves resistance to the weather and camera shake, optimizing the noise caused by background region revealed.