GMM 混合高斯背景建模

混合高斯背景建模，可以把连续帧图片前景与背景区分开来

clc;
clear all;
I=imread（‘0000.jpg‘）;                                                                       % 读入第一帧作为背景帧
fr_bw = rgb2gray（I）;     
[heightwidth] = size（fr_bw）;                                                               %求每帧图像大小
C=3;                                                                                        % 单高斯模型的个数（通常为3-5）
u0 = zeros（heightwidthC）;
for i= 1:C-1
    u0（::i） = double（I（::i））;%255*double（I（::i））./double（sum（I3）+（1e-10））;
end
u0（::C）=double（fr_bw）; 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%设置初始参数%%%%%%%%%%%%%%%%%%%%%%
M = 3;                                                                                      % 代表背景的模型个数
T = 5;
D = 2.5;                                                                                    % 偏差阈值
alpha = 0.001;                                                                              % 学习率
thresh = 0.5;                                                                               % 前景阈值
sd0 = 15;                                                                                   % 初始化标准差
w = ones（heightwidthC）/C;                                                                 % 初始化权重矩阵
sd = sd0*ones（heightwidthC）;                                                              % 像素标准差
p = alpha./w;                                                                               % 初始化p变量，用来更新均值和标准差
rank = zeros（1C）;                                                                          %各个高斯分布的优先级（w/sd）
frame_num=200;                                                                              %帧数
for n = 1:frame_num
    if n<10
        a=‘000‘;
    end
    if n<100&&n>=10
        a=‘00‘;
    end
    if 100<=n
        a=‘0‘;
    end

    frame=strcat（anum2str（n）‘.jpg‘）;
    I1=imread（frame）;                                                                       % 依次读入各帧图像
    fr_bw0 =rgb2gray（I1）;
%     fr_bw0=medfilt2（fr_bw0[3 3]）;
    h=fspecial（‘average‘）;
    fr_bw0=imfilter（fr_bw0h）;
    for i= 1:C-1
        fr_bw（::i） = double（I1（::i））;%255*double（）./double（sum（I13）+（1e-10））;
    end
    fr_bw（::C）=double（fr_bw0）;
    for i= C+1:M
        fr_bw（::i） = double（fr_bw0）;
    end
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 计算新像素与高斯模型均值的绝对距离%%%%%%%%%%%%%
    u_diff = abs（double（fr_bw） - double（u0））;
     
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 更新高斯模型的参数%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    match0=abs（u_diff）<=max（D*sdT）;                                                        %像素与高斯模型匹配则标注为1，否则为0
    match=max（match0[]3）;                                                                 %判断是否有高斯分布与图像匹配
    p=alpha./w;                                                                             %更新p
    wmatch1=（1-alpha）*w.*match0 + alpha.*match0;                                            %若更新匹配部分的w
    wmatch0 = （1-alpha）*w.*（1-match0）;                                                      %若更新不匹配部分的w
 

 属性            大小     日期    时间   名称
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     文件        5072  2012-01-08 05:23  GMM.m