[1]李庆武,蔡艳梅,徐立中.基于分块分类的智能视频监控背景更新算法[J].智能系统学报,2010,5(3):272-276.
　LI Qing-wu,CAI Yan-mei,XU Li-zhong.Background update algorithm based on blocks classification forintelligent video surveillance[J].CAAI Transactions on Intelligent Systems,2010,5(3):272-276.
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基于分块分类的智能视频监控背景更新算法

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 5 期数: 2010年第3期 页码: 272-276 栏目: 学术论文—机器感知与模式识别 出版日期: 2010-06-25
Title:
Background update algorithm based on blocks classification forintelligent video surveillance
文章编号:
1673-4785(2010)03-0272-05
作者:
李庆武，蔡艳梅，徐立中
河海大学 计算机及信息工程学院，江苏 常州 213022
Author(s):
LI Qing-wu, CAI Yan-mei, XU Li-zhong
College of Computer and Information Engineering, Hohai University, Changzhou 213022, China
关键词:
图像处理; 智能视频监控; 背景差分; 分块; 背景更新
Keywords:
image processing;  intelligent video surveillance;  background subtraction;  blocks classification;  background update
分类号:
TP391.4；TN991.73
文献标志码:
A
摘要:
针对传统智能视频监控中背景更新算法计算量大、对光照变化敏感等问题，提出了一种基于分块分类的背景更新算法.首先，根据视频序列获得初始的背景参考图像，采用背景差分法得到当前帧的差分图像.然后，将差分图像采用分块处理，按照子块的均值特征对各子块图像进行前景块和背景块的分类.最后，根据分类情况采用不同的背景更新策略，实现背景的实时更新.该算法以块为操作对象，相比单个像素处理时的计算量更小，运算速度更快.实验结果表明，新算法能较好地适应光照变化，背景更新效果较好.
Abstract:
Background update algorithms have excessive calculation overhead and are sensitive to changes in lighting. In order to solve these problems, a background update algorithm based on block classification was proposed. First, image differences were obtained by subtracting the incoming frame from the reference image. Then the image differences were divided into blocks of equal size. Each block was then classified as a background block or a foreground block according to the blocks’ predominant features. Different updating strategies were then employed according to the classification of the block. In this way, realtime background updates were possible. This algorithm overcame problems of computational redundancy arising in other pixelbackground models. Execution speed was improved because objectoperations were performed on every block. Experimental results showed that this method well adapts to changes in illumination. 
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备注/Memo

收稿日期：2009-02-11.
基金项目：国家自然科学基金资助项目（60972101）；国家“863”计划资助项目（2007AA11Z227）；江苏省社会发展科技项目（BS2007058）.
通信作者：李庆武.E-mail:li_qingwu@163.com.
作者简介：
李庆武，男，1964年生，教授、博士生导师、博士，中国光学学会光电技术专业委员会委员，中国电子学会高级会员.主要研究方向为数字图像处理、智能信息系统.主持和参与国家和省部级科技计划项目6项，发表学术论文50余篇.
蔡艳梅，女，1981年生，硕士研究生，主要研究方向为数字图像处理.
徐立中，男，1958年生，教授、博士生导师、博士，主要研究方向为信息获取与处理、遥测遥控、智能信息系统.主持和完成国家和省部级科技计划项目9项，发表学术论文100余篇，出版专著4部.

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