MATLAB自适应阈值分割

%本程序是利用最大类间方差算法求解自适应阈值，对图像进行分割 clear; warning off; I=imread('1807i.bmp'); %rgb转灰度 if isrgb(I)==1 I_gray=rgb2gray(I); else I_gray=I; end figure,imshow(I_gray); I_double=double(I_gray);%转化为双精度 [wid,len]=size(I_gray); colorlevel=256; %灰度级 hist=zeros(colorlevel,1);%直方图 %threshold=128; %初始阈值 %计算直方图 for i=1:wid for j=1:len m=I_gray(i,j)+1; hist(m)=hist(m)+1; end end hist=hist/(wid*len);%直方图归一化 miuT=0; for m=1:colorlevel miuT=miuT+(m-1)*hist(m); end xigmaB2=0; for mindex=1:colorlevel threshold=mindex-1; omega1=0; omega2=0; for m=1:threshold-1 omega1=omega1+hist(m); end omega2=1-omega1; miu1=0; miu2=0; for m=1:colorlevel if m<threshold miu1=miu1+(m-1)*hist(m); else miu2=miu2+(m-1)*hist(m); end end miu1=miu1/omega1; miu2=miu2/omega2; xigmaB21=omega1*(miu1-miuT)^2+omega2*(miu2-miuT)^2; xigma(mindex)=xigmaB21; if xigmaB21>xigmaB2 finalT=threshold; xigmaB2=xigmaB21; end end fT=finalT/255 %阈值归一化 T=graythresh(I_gray)%matlab函数求阈值 for i=1:wid for j=1:len if I_double(i,j)>finalT bin(i,j)=1; else bin(i,j)=0; end end end figure,imshow(bin); figure,plot(1:colorlevel,xigma);