摘要
背景差法是一种重要的运动检测方法,其难点在于如何进行背景更新.针对该问题,提出一种基于像素灰度归类的背景重构算法,即在假设背景像素灰度以最大概率出现在图像序列的前提下,利用灰度差对相应像素点灰度进行归类,选择频率最高的灰度值作为该点的背景像素值.在背景缓慢变化和突变时,分别利用该算法进行定时和实时背景重构具有明显的优点.仿真结果表明,即使场景中存在运动前景,该算法也能够准确地重构背景,并有效地避免混合现象,从而实现对运动目标的完整提取,以便进一步识别或跟踪.
The background subtraction is an important method to detect the moving objects, and its difficulty is the background update. So a background reconstruction algorithm based on pixel intensity classification is presented in this paper. According to the hypothesis that the background pixel intensity appears in image sequence with maximum probability, the pixel intensity differences between sequential two frames are calculated, and the intensity values at the pixels are classified by means of these differences. For the new algorithm, neither the pre-training of the background without any moving target, nor the models of background and targets are needed. Simulation results indicate that background can be reconstructed correctly by using the new algorithm, so the target can be extracted perfectly and tracked successfully.
出处
《软件学报》
EI
CSCD
北大核心
2005年第9期1568-1576,共9页
Journal of Software
基金
国家重点基础研究发展规划(973)~~
关键词
背景差
背景重构
运动检测
图像分割
跟踪
视频监视
background subtraction
background reconstruction
motion detection
image segmentation
tracking
visual surveillance
作者简介
侯志强（1973-），男，陕西眉县人，博士，副教授，主要研究领域为图像处理，计算机视觉，信息融合；
韩崇昭（1943-），男，教授，博士生导师，主要研究领域为随机与自适应控制，非线性系统，多源信息融合.
