harrismain.rar_harris recognition_matlab cloth image_小波变换harris_

clc,close all,clear for i =4:4 str = ['..\检测图片\布匹5.6\' num2str(i) '-1.bmp']; I=imread(str); % J=rgb2gray(I); % figure,imshow(J) H=histeq(I); % figure,imshow(H) [X,map]=gray2ind(H,256); figure,subplot(4,4,1); image(I); colormap(map); title('原始图像'); subplot(4,4,2); image(H); colormap(map); title('灰度均衡化图像'); %使用db4对X进行尺度为3的分解 [c,s]=wavedec2(X,2,'db8'); %从小波分解结构[c，s]进行尺度为2的高频重构 hd3=wrcoef2('h',c,s,'db8',1); vd3=wrcoef2('v',c,s,'db8',1); subplot(4,4,5); image(hd3); colormap(map); title('尺度为2时的水平高频图像'); subplot(4,4,6); image(vd3); colormap(map); title('尺度为2时的垂直高频图像'); %水平方向高频图像的特征值 for i=1:64 dwin(:,:,i)=hd3((4*i-3):4*i,1:256); %计算四个特征值：能量、方差、熵、极差 energy(i)=mean(mean(dwin(:,:,i))); std(i)=std2(dwin(:,:,i)); ent(i)=entropy(dwin(:,:,i)); M(i)=sum(range(dwin(:,:,i))); end % for i=1:32 % dwin(:,:,i)=hd3((8*i-7):8*i,1:256); % %计算四个特征值：能量、方差、熵、极差 % energy(i)=mean(mean(dwin(:,:,i))); % std(i)=std2(dwin(:,:,i)); % ent(i)=entropy(dwin(:,:,i)); % M(i)=sum(range(dwin(:,:,i))); % end subplot(4,4,9); plot((energy-mean(energy))/(max(energy-min(energy)))); axis([0 64 (-1) 1]); title('水平 能量'); subplot(4,4,10); plot((std-mean(std))/(max(std)-min(std))); axis([0 64 (-1) 1]); title('水平 方差'); subplot(4,4,11); plot((ent-mean(ent))/(max(ent)-min(ent))); axis([0 64 (-1) 1]); title('水平 熵'); subplot(4,4,12); plot((M-mean(M))/(max(M)-min(M))); axis([0 64 (-1) 1]); title('水平 极差'); %垂直方向高频图像的特征值 for k=1:64 dwin1(:,:,k)=vd3(1:256,(4*k-3):4*k); %计算四个特征值：能量、方差、熵、极差 energy1(k)=mean(mean(dwin1(:,:,k))); std1(k)=std2(dwin1(:,:,k)); ent1(k)=entropy(dwin1(:,:,k)); M1(k)=sum(range(dwin1(:,:,k))); end % for k=1:32 % dwin1(:,:,k)=vd3(1:256,(8*k-7):8*k); % %计算四个特征值：能量、方差、熵、极差 % energy1(k)=mean(mean(dwin1(:,:,k))); % std1(k)=std2(dwin1(:,:,k)); % ent1(k)=entropy(dwin1(:,:,k)); % M1(k)=sum(range(dwin1(:,:,k))); % end subplot(4,4,13); plot((energy1-mean(energy1))/(max(energy1-min(energy1)))); axis([0 64 (-1) 1]); title('垂直 能量'); subplot(4,4,14); plot((std1-mean(std1))/(max(std1)-min(std1))); axis([0 64 (-1) 1]); title('垂直 方差'); subplot(4,4,15); plot(( ent1-mean( ent1))/(max( ent1)-min( ent1))); axis([0 64 (-1) 1]); title('垂直 熵'); subplot(4,4,16); plot((M1-mean(M1))/(max(M1)-min(M1))); axis([0 64 (-1) 1]); title('垂直 极差'); end