• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (06): 1220-1224.

• 论文 • 上一篇    下一篇

基于码本和运行期均值法的双层背景建模方法

刘妍江,智敏   

  1. (内蒙古师范大学计算机与信息工程学院,内蒙古 呼和浩特 010022)
  • 收稿日期:2015-01-06 修回日期:2015-08-26 出版日期:2016-06-25 发布日期:2016-06-25

A twolayer background modeling method
based on codebook and running average  

LIU Yanjiang,ZHI Min   

  1. (College of Computer and Information Engineering,Inner Mongolia Normal University,Hohhot 010022,China)
  • Received:2015-01-06 Revised:2015-08-26 Online:2016-06-25 Published:2016-06-25

摘要:

背景建模是视频处理的重要部分,是后续运动目标检测、识别和跟踪的基础。针对现有的背景建模方法无法兼顾抗干扰性、适应光照、背景更新速度和遮挡等问题,提出结合码本和运行期均值法对视频进行双层背景建模的方法。首先在第一层提取亮度和颜色特征,使用聚类的方法进行码本建模,接着在第二层建立运行期均值法模型,通过两种背景模型的有效结合快速准确地实现运动目标分割。实验结果表明,该背景建模方法计算简单、背景更新快、抗噪声能力强并且能较好地适应光照变化,适应于复杂环境下的目标检测。

关键词: 背景建模, 码本, 运行期均值法, 分割, 抗噪声能力

Abstract:

Background modeling is a critical task in video processing, and it is the foundation of subsequent detection, recognition and tracking of moving objects. Considering the existing problems in background modeling methods, we propose a twolayer background model method based on codebook and running average. Firstly, we extract brightness and color features in the first layer and build the codebook model using the method of clustering. Then in the second layer we construct the running average model, and  through the effective combination of the two background models we achieve a fast and accurate moving object segmentation. Experimental results show that the background modeling method has advantages of low computation complexity, strong antinoise ability and fast background update speed, and it can also adapt to light change, thus applicable to moving object detection in complex environments.

Key words: background modeling;codebook;running average;segmentation;antinoise ability