一种有效的两阶段视频图像处理方法  

An Effective Two-phase Method for Video Image Processing

作　　者：蒋明[1] 潘姣丽[1] 

机构地区：[1]西安电子科技大学计算机学院,陕西西安710071

出　　处：《微电子学与计算机》2011年第4期159-161,166,共4页Microelectronics & Computer

基　　金：国家自然科学基金项目(60772317);陕西省自然科学基础研究计划项目(2006F30)

摘　　要：传统混合高斯模型是背景估计中常用的方法,但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,从而造成了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,即所谓的空洞问题.文中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.通过实验表明,采用该两阶段视频图像处理方法能明显的改善背景建模的速度,也能有效的解决提取目标出现的空洞问题,从而验证了该算法的有效性.The traditional mixture Gaussian model is a commonly used method in background estimation, however, 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 the 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 the problem, we propose an effective two--phase method for video images processing. In the first phase, this method automatically adjusts the number of Gaussian distribu tion based on the priority of each pixel; in the second phase, it firstly partitions the area of each pixel, then uses dif- ferent update method for object area and non--object area. The experiments show that the two--phase method for video image processing can significantly improve the speed of background model, furthermore efficiently resolve the empty problem in extracting objects, so it verifies the effective of the method.

关 键 词：背景建模 混合高斯模型 背景更新 目标检测 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]