Edge Detection - Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques - page 187

mem1=(img1-mn)./(mx-mn);
mun=[];
% computing optimum value of 'constant' in intuitionistic fuzzy
generator
for con=0.1:0.2:10
mem= 1-(1-mem1).^con;
nonmem=(1-mem1).^(con*(con+1));
hes=1-mem-nonmem;
u=0.0;
for i=1:dim
for j=1:dim
ent= (2*mem(i,j)*nonmem(i,j)+hes(i,j)^2)/(hes(i,j)^2+
mem(i,j)^2+ nonmem(i,j)^2) + u;
u=ent;
end
end
lin=ent;
lin_ind=[mun;lin];
mun=lin_ind;
lin_ind;
end
lin_ind
l=max(lin_ind);
[con]=find(l==lin_ind);
fincon= 0.1+(con-1)*0.2 % the constant term
% computing membership and nonmembership function of an
intuitionistic fuzzy image
int_mem =1-(1-mem1).^fincon;
nonmem = (1-mem1).^(fincon*(fincon+1));
hes = 1-int_mem-nonmem;
img = int_mem;
% median calculation in 3x3 window
row =dim;col=dim;
% replicate the edge pixels
edgim=zeros(dim,dim);
dim11=dim+1;dim21=dim+1;
edgimage=zeros(dim11,dim21);
r1=img(2,:);r2=img(row-1,:);c1=img(:,2);c2=img(:,col-1);
bor1=[0,r1,0];bor2=[0,r2,0];
p1=[c1,img,c2];f2=[bor1;p1;bor2];
f2(1,1)=img(1,1);f2(row+2,col+2)=img(row,col);f2(1,col+2)=img(1,col);
f2(row+2,1)=img(row,1);
for i=2:dim11
for j=2:dim21
im=[f2(i-1,j-1),f2(i,j-1),f2(i+1,j-1);...
f2(i-1,j),f2(i,j),f2(i+1,j);...
f2(i-1,j+1),f2(i,j+1),f2(i+1,j+1)];
cropim1=im(:);
med_im=median(cropim1);