基于图像处理的裂缝宽度检测系统-matlab

clc clear I=imread('4.JPG'); p=rgb2gray(I); %I1=uint8(p); I1=p; I2=I1; I1=double(I1); %将最边缘的地方设定为黑色；然后以梯度值(即像素值差值)代替种子元素 [H,L]=size(I1); for i=2:H-1 for j=2:L-1 %prewitt算子； a(i,j)=abs(I1(i+1,j+1)+I1(i,j+1)+I1(i-1,j+1)-I1(i-1,j-1)-I1(i,j-1)-I1(i+1,j-1));%Gy b(i,j)=abs(I1(i+1,j+1)+I1(i+1,j)+I1(i+1,j-1)-I1(i-1,j-1)-I1(i-1,j)-I1(i-1,j+1));%Gx I2(i,j)=sqrt(b(i,j)^2+a(i,j)^2); end end for j=1:H I2(j,1)=0; end for j=1:H I2(j,L)=0; end for i=2:L-1 I2(1,i)=0; end for i=2:L-1 I2(H,i)=0; end %figure,imshow(I2) maxvalue=max(max(I2)); T=maxvalue %T值变动,遍历I2,取得最大值，赋值于T I2=double(I2);%转换数据类型，方便后边计算 T*0.6;%选定一个阈值,然后将梯度图像进行二值化,只有0、1值 I2=im2bw(I2/255,0.7);%代替以下的for循环 %imshow(I2); %I1是灰度图像，矩阵对应元素相乘： %将I1转换成double型 I3=I2.*I1; %代替以下for循环 I3=uint8(I3); imshow(I3); %取出I3的最大类间阈值T2 %T2=graythresh(I3); Totalvalue=sum(I3(:));%各个像素值求和 %Nozero=numel(I3(:,:)>0);%非0像素的个数 Totalvalue I3=double(I3); clc3=tabulate(I3(:)); numel=sum(clc3(:,2))-clc3(1,2) Megray=Totalvalue/numel [H1,L1]=size(clc3); hist=clc3(2:H1,3); valid=clc3(2:H1,1); hist=hist*640*480/numel/100 colorlevel=255; xigmaB2=0; valid for t=1:colorlevel threshold=t; p1=0; p2=0; for i=1:H1-1 if valid(i)<=threshold p1=p1+hist(i); end end p2=1-p1; lowmean=0; upmean=0; for i=1:H1-1 if valid(i)<=threshold lowmean =lowmean+valid(i)*hist(i); else upmean=upmean+valid(i)*hist(i); end end lowmean=lowmean/p1; upmean=upmean/p2; xigmaB21=p1*(lowmean-Megray)^2+p2*(upmean-Megray)^2; xigma(t)=xigmaB21; if xigmaB21>xigmaB2 p1 finalT=threshold xigmaB2=xigmaB21; end end I4=im2bw(I1/255,finalT/255); imshow(I4);