folder.zip_图像处理_步态识别

clc,clear nStar = 1; nNUM = 200; Background = double( rgb2gray(imread( [ 'person',int2str(nStar),'.bmp']) )); for k = nStar+1 :1: nNUM CurrentImage =double(rgb2gray(imread( [ 'person',int2str(k),'.bmp'] ))); FormerImage =double(rgb2gray(imread( [ 'person',int2str(k-1),'.bmp'] ))); ID =uint8(abs( CurrentImage - FormerImage )); % 选择阈值 T=yuzhi(ID); BW = im2bw(ID,T/255); % 更新背景 alpha = 0.00001; CurrentBack = Background.*BW + ( alpha.* CurrentImage + ( 1-alpha ).* Background ).*( 1 -BW ); Background = CurrentBack; Cut=abs(CurrentImage-Background); Cut=uint8(Cut); Tcut=yuzhi(Cut); BWCut=im2bw(Cut,Tcut/255); SE=[1 1 1;1 1 1;1 1 1]; BWCutero=imerode(BWCut,SE); BWCuterodil = bwmorph(BWCutero,'dilate',3); figure(1),imshow(BWCuterodil),title('差分后图像') imwrite(BWCuterodil,strcat('rgb',num2str(k),'.bmp'),'bmp'); figure(2),imshow(imread( [ 'car',int2str(k),'.bmp'] )) [L,nm] = bwlabel(BWCuterodil,8); for i = 1:nm [r,c] = find(L == i); left= min(c); right= max(c); top= min(r); buttom= max(r); width=right - left + 1; height = buttom - top + 1; rectangle('Position',[left,top,width,height],'EdgeColor','r');%对车辆用矩形标记 pause(0.01); %0.01 end end