生物技术

开发平台：
Matlab

complete code.txt：源码内容
							load anonymous.mat;
load im1.mat;
load im2.mat;
load im3.mat;
%data conversion of the 'pct' provided images
convert1=fopen('villain_1.pct');                  
char=fread(convert1,297,'char');                
unit8=fread(convert1,[512 512],'uint8');                 
transpose=unit8';                                                  
convert1=fopen('villain_2.pct');                  
char=fread(convert1,297,'char');                
unit8=fread(convert1,[512 512],'uint8');                 
transpose1=unit8';                                                  
convert1=fopen('villain_3.pct');                  
char=fread(convert1,297,'char');                
unit8=fread(convert1,[512 512],'uint8');                 
transpose2=unit8';                                                  
subplot(2,3,2),imshow(crime),title('corrupted fingerprint');
subplot(2,3,4),imshow(transpose,[0 255]),title('villain1');
subplot(2,3,5),imshow(transpose1,[0 255]),title('villain2');
subplot(2,3,6),imshow(transpose2,[0 255]),title('villain3');
%filtration of noise involved
filt1=medfilt2(crime,[5 5],'symmetric');
filt2=ordfilt2(filt1,5,ones(3,3));
filt3=medfilt2(filt2,[4 4],'symmetric');
threshold=graythresh(filt3);
conversion=im2bw(filt3,threshold);
figure,subplot(2,2,1),imshow(filt1),title('5x5 median filter');
subplot(2,2,2),imshow(filt2),title('ordinary filter');
subplot(2,3,5),imshow(filt3),title('4x4 median filter');
%to extract the size and location features
construct=strel('square',4);
close=imclose(conversion,construct);
close1=imclose(close,construct);
[M,N]=find(close1==0);
T=min(min(M));
B=max(max(M));
L=min(min(N));
R=max(max(N));
RA1=(B-T)/2;
RA2=(R-L)/2;
if(RA1>=RA2)
    RA=RA2;
else
    RA=RA1;
end
X=L+RA;
Y=T+RA;
[m,n] = size(crime);
CI=zeros([m,n]);
for N=1:m
  for M=1:n
    if((N-X)^2+(M-Y)^2<=RA^2)
        CI(M,N)=1;
    end
  end
end
CI1=CI.*double(filt2);
CI1=uint8(CI1);
rotation=imrotate(CI1,-30,'crop');
divide=RA/1.414;
divide=fix(divide);
RO=rotation((Y-divide):(Y+divide),(X-divide):(X+divide));
figure,subplot(2,2,1),imshow(close),title('Morphological close');
subplot(2,2,2),imshow(CI),title('Circle in black square');
subplot(2,2,3),imshow(CI1),title('Combination');
subplot(2,2,4),imshow(RO),title('Feature extraction');
%feature matching of the corrupted and archived fingerprints
filt1=medfilt2(crime,[5 5], 'symmetric');
filt2=medfilt2(crime,[7 7], 'symmetric');
filt3=ordfilt2(filt1,5,ones(3 ,3));
mod=medfilt2(filt3,[4 4]);
ba=find(mod>130 & filt2<140); 
[r,c]=size(mod);
ar=r*c;
ci= ar-length(ba);
ra=sqrt(ci/pi);
ra=round(ra);
mod=double(mod);
fc=mod ./255;
im=ci .* fc;
S=2*ra*cos(pi/4);
S=round(S);
rotation=imrotate(im,-30,'bilinear');
[r,c]=size(rotation);
Ee=round((c+1)/2);
Tt=round((r+1)/2);
b=Ee-(S/2);
i=Tt-(S/2);
b=round(b);
i=round(i);
region=imcrop(rotation,[b, i, S, S]);
cc1= zeros(356);
for col=1:356     
    for row=1:356
        cc1(row,col)=corr2(region, im1(row:row+156, col:col+156)); 
    end
end
maximum1=max(max(cc1));
maximum1         
cc2= zeros(356);
for col=1:356
    for row=1:356
        cc2(row,col)=corr2(region, im2(row:row+156, col:col+156));
    end
end
maximum2=max(max(cc2));
maximum2
cc3=zeros(356);
for col=1:356
    for row=1:356
        cc3(row,col)=corr2(region,im3(row:row+156, col:col+156));
    end
end
maximum3=max(max(cc3));
maximum3
if(maximum1>=maximum2)
    maximum=maximum1;
    [row,col]=find(cc1==maximum);
    res=im1(row:row+S, col:col+S);
    figure, imshow(res), title('Matching Villain 1');
else
    maximum=maximum2;
    [row,col]=find(cc2==maximum);
    res=im2(row:row+S, col:col+S);
    figure, imshow(res), title('Matching Villain 2');
end
if(maximum>=maximum3)
    maximum=maximum
else maximum=maximum3;
    [row,col]=find(cc3==maxm);
    res=im3(row:row+S,col:col+S);
    figure, imshow(res), title('Matching Villain 3');
end
%feature classification of the matching found and the processed fingerprint
region=RO;
 [m n]=size(RO);
 if (maximum1>=maximum2)
 maximum=maximum1;
    [row,col] = find(cc1==maximum);
   res=im1(row:row+m,col:col+n);
   figure,imshow(res),title('Matching Villain 1');
   else
    maximum=maximum2;
    [row,col] = find(cc2==maximum);
   res=im2(row:row+m,col:col+n);
   figure,imshow(res),title('Matching Villain 2');
   end
if( maximum>=maximum3)
    maximum=maximum;
else
    maximum=maximum3;
     [row,col] = find(cc3==maximum);
  res=im3(row:row+m,col:col+n);
  figure,imshow(res),title('Matching Villain 3');
  end
SUBPLOT(1,2,1),imshow(region);title('After processing');
SUBPLOT(1,2,2),imshow(res);title('After matching');

						