一种改进的混合高斯模型背景估计方法

传统混合高斯模型一般为每个像素分配固定的高斯分布个数,从而造成背景形成速度的减慢和系统资源的浪费;同时也存在着高斯模型背景建模中的缓慢或滞留运动物体造成目标误判现象的问题(即空洞问题)。为此,提出了一种有效的两阶段视频图像处理方法。该方法在第一阶段根据像素点的优先级大小自动地调节高斯分布的数目,在第二阶段首先对像素点进行所属区域的划分,进而对目标区域和非目标区域采取不同的更新手段。实验表明,采用两阶段视频图像处理方法明显地改善了背景建模的速度,有效解决了提取目标出现的空洞问题。

An improved method of mixture Gaussian model for background estimation

The traditional mixture Gaussian model always allocates a fixed number of Gaussian distribution for each pixel. Thus, it causes the slowdown of the background germinate speed and waste of system resource Meanwhile, it exists that the object misjudge phenomenon, namely empty problem, caused by slowdown or demurrage of moving object in the modeling of Gaussian model background. To solve these problems, the paper proposes an effective two-phase method for video images processing. In the first phase, this metho...