图像特征提取matlab程序

%直接帧间差分，计算阈值并进行二值化处理（效果不好）

clc;

clear;

Im1 = double(imread('')); %读取背景图片

Im2 = double(imread(''); %读取当前图片

[X Y Z] = size(Im2); %当前图片的各维度值DIma = zeros(X,Y);

for i = 1:X

for j = 1:Y

DIma(i,j) =Im1(i,j) - Im2(i,j); %计算过帧间差分值 end

end

figure,imshow(uint8(DIma)) %显示差分图像

title('DIma')

med = median(DIma); %计算二值化阈值：差值图像中值mad = abs(mean(DIma) - med); %中值绝对差

T = mean(med + 3**mad) %初始阈值

Th =5*T; %调整阈值

BW = DIma <= Th; %根据阈值对图像进行二值化处理figure,imshow(BW)

%se = strel('disk',2); %膨胀处理

%BW = imopen(BW,se);

%figure,imshow(BW)

%title('BW')

[XX YY] = find(BW==0); %寻找有效像素点的最大边框

handle = rectangle('Position',[min(YY),min(XX) ,max(YY)-min(YY),max(XX)-min(XX)]);

set(handle,'EdgeColor',[0 0 0]);

hei = max(XX)-min(XX); %边框高度

mark = min(YY)+1;

while mark < max(YY)-1 %从边框左边开始到右边物质循环，寻找各个人体边缘

left = 0;right = 0;

for j = mark:max(YY)-1

ynum = 0;

for i = min(XX)+1 : max(XX)-1

if BW(i,j) == 0;

ynum = ynum + 1;

end

end

if ynum > *hei %如果该列上像素点个数大于边框高度的某个阈值

left = j %认为找到了左边界

mark = j;

break

end

end

if left~= 0 %如果找到了左边界

for j = left+1 : max(YY)-1 %则从左边界到边框右边界寻找人体右边界

ynum = 0;

for i = min(XX)+1 : max(XX)-1

if BW(i,j) == 0;

ynum = ynum + 1;

end

end

if ynum < *hei %如果该列上像素点个数小于边框高度的某个阈值

right= j %认为找到了左边界

mark = j;

break

end

end

if left~=right %如果左右边界值不相等，即同时找到了左右边界，继续以左右边界为界寻找上下边界

[top,bottom] = Find_edge(BW,min(XX)+1,max(XX),left,right,;

handle = rectangle('Position',[left,top,right-left,bottom-top]);

set(handle,'EdgeColor',[0 0 0]); %显示图像中人体有效边界

end

end

mark = mark + 1;

end % while