I have a fingerprint recognition code in MATLAB in which for which I want detail explanations, all the function used inside this code is cleared to me

% EXTRACTING FEATURE FROM A FINGERPRINT IMAGE
%
% Usage:  [ ret ] = ext_finger( img, display_flag );
%
% Argument:   img - FingerPrint Image
%             display_flag
%               
% Returns:    ret - Minutiae
function [ ret ] = ext_finger( img, display_flag )
    if nargin==1; display_flag=0; end
    block_size_c = 24; YA=0; YB=0; XA=0; XB=0;
% Enhancement -------------------------------------------------------------
    if display_flag==1; fprintf(' >>> enhancement '); end
    yt=1; xl=1; yb=size(img,2); xr=size(img,1);
    for x=1:55
        if numel(find(img(x,:)<200)) < 8
           img(1:x,:) = 255;
           yt=x;
        end
    end
    for x=225:size(img,1)
        if numel(find(img(x,:)<200)) < 3
           img(x-17:size(img,1),:) = 255;
           yb=x;
           break
        end
    end
    for y=200:size(img,2)
        if numel(find(img(:,y)<200)) < 1
           img(:,y:size(img,2)) = 255;
           xr=y;
           break
        end
    end
    for y=1:75
        if numel(find(img(:,y)<200)) < 1
           img(:,1:y) = 255;
           xl=y;
        end  
    end
    imshow(img);
    figure(2);
    [ binim, mask, cimg, cimg2, orient_img, orient_img_m ] = f_enhance(img);
% Making Mask -------------------------------------------------------------
    if display_flag==1; fprintf('done.\n >>> making mask '); end
    mask_t=mask;
    for y=19:size(mask,1)-block_size_c*2
        for x=block_size_c:size(mask,2)-block_size_c*2
          n_mask = 0;
          for yy=-1:1
              for xx=-1:1
                  y_t = y + yy *block_size_c; 
                  x_t = x + xx *block_size_c; 
                  if y_t > 0 && x_t > 0 && (y_t ~= y || x_t ~= x) && mask(y_t,x_t) == 0
                     n_mask = n_mask + 1;
                  end
              end
          end 
          if n_mask == 0
             continue 
          end
          if mask(y,x) == 0 || y > size(mask,1) - 20  ||  y < yt || y > yb || x < xl || x > xr
               cimg2(ceil(y/(block_size_c)), ceil(x/(block_size_c))) = 255;
               mask_t(y,x) = 0;
               continue;
          end
          for i = y:y+1
            for j = x-9:x+9
              if i > 0 && j > 0 && i < size(mask,1) && j < size(mask,2) && mask(i,j) > 0
              else
                 cimg2(ceil(y/(block_size_c)), ceil(x/(block_size_c))) = 255;
                 mask_t(y,x)=0;
                 break
              end
            end
          end
        end
    end
    mask=mask_t;
    inv_binim = (binim == 0);
    thinned =  bwmorph(inv_binim, 'thin',Inf);
    mask_t=mask;
    if numel(find(mask(125:150,150:250)>0)) > 0 && numel(find(mask(250:275,150:250)>0)) > 0
      mask(150:250,150:250)=1;
    end
    method=-1; core_y = 0; core_x = 0; core_val=0; lc=0;
    o_img=sin(orient_img); o_img(mask == 0) = 1;

      lower_t=0.1;
      [v,y]=min(cimg);
      [dt1,x]=min(v);
      delta1_y=y(x)*block_size_c/2; delta1_x=x*block_size_c/2;

      v(x)=255; v(x+1)=255;
      [dt2,x]=min(v);
      delta2_y=y(x)*block_size_c/2; delta2_x=x*block_size_c/2;

      v(x)=255; v(x+1)=255;
      [dt3,x]=min(v);
      delta3_y=y(x)*block_size_c/2; delta3_x=x*block_size_c/2;

      db=60;
      if dt1 < 1 && delta1_y+db < core_y && delta1_y > 15 || dt2 < 1 && delta2_y+db < core_y && delta2_y > 15 || dt3 < 1 && delta3_y+db < core_y && delta3_y > 15 
          core_val=255;
      end
      for y=10:size(o_img,1)-10
          for x=10:size(o_img,2)-10
              s1=0; t=10; %few of bad cores here 
              if y < 50 && x > 250
                 t=11; 
              end
              if y > 38
                 yt=20;
              else
                 yt=5;
              end
              if lc > 0.41 && (core_y + 60 < y)
                 break;
              end
              if mask(y,x)==0 || mask(max(y-t,1),x)==0 || mask(y,min(x+t, size(o_img,2)))==0 || mask(y,max(x-t,1))==0 || mask(max(y-t,1),min(x+t,size(o_img,2)))==0 || mask(max(y-t,1),max(x-t,1))==0 || o_img(y,x) < lc || o_img(y,x) < 0.1 
                 continue
              end  
              if dt1 < 1 && delta1_y+db < y && delta1_y > 15 || dt2 < 1 && delta2_y+db < y &&    delta2_y > 15 || dt3 < 1 && delta3_y+db < y && delta3_y > 15 
                 continue
              end
              test_m=min(o_img(1:y-yt,max((x-10),1):min(x+10,size(o_img,2)) ));
              if numel(test_m)>0 && min(test_m) >= 0.17
                 continue
              end 
              for a=y:y+2 
                  for b=x:x+1
                      s1=s1+o_img(a,b);    
                  end
              end
              s1=s1/6; s2=[]; i=1;
              for a=y-3:y-1
                  for b=x:x+1
                      s2(i)=o_img(a,b);    
                      i=i+1;
                  end
              end
              if min(s2) < lower_t
                 s2=sum(s2)/6;       
              else 
                 s2=s1;
              end
              s3=[]; i=1;
              for a=y:y+2 
                  for b=x+2:x+3
                      s3(i)=o_img(a,b);    
                      i=i+1;
                  end
              end
              if min(s3) < lower_t
                 s3=sum(s3)/6;       
              else  
                 s3=s1;
              end
              s4=[]; i=1;
              for a=y:y+2 
                  for b=x-2:x-1
                      s4(i)=o_img(a,b);    
                      i=i+1;
                  end
              end
              if min(s4) < lower_t
                 s4=sum(s4)/6;       
              else 
                 s4=s1;
              end
              s5=[];
              i=1;
              for a=y-3:y-1 
                  for b=x-2:x-1
                      s5(i)=o_img(a,b);    
                      i=i+1;
                  end
              end
              if min(s5) < lower_t
                 s5=sum(s5)/6;       
              else 
                s5=s1;
              end
              s6=[]; i=1;
              for a=y-3:y-1 
                  for b=x+2:x+3
                      s6(i)=o_img(a,b);    
                      i=i+1;
                  end
              end
              if min(s6) < lower_t
                s6=sum(s6)/6;       
              else 
                s6=s1;
              end
              if s1-s2 > core_val
                 core_val=s1-s2;
                 core_x=x;
                 core_y=y;
                 lc=o_img(y,x);
                 method=1;
              end 
              if s1-s3 > core_val
                 core_val=s1-s3;
                 core_x=x;
                 core_y=y;
                 lc=o_img(y,x);
                 method=2;
              end 
              if x < 300 && s1-s4 > core_val
                 core_val=s1-s4;
                 core_x=x;
                 core_y=y;
                 lc=o_img(y,x);
                 method=3;
              end 
              if x < 300 && s1-s5 > core_val
                 core_val=s1-s5;
                 core_x=x;
                 core_y=y;
                 lc=o_img(y,x);
                 method=4;
              end 
              if s1-s6 > core_val
                 core_val=s1-s6;
                 core_x=x;
                 core_y=y;
                 lc=o_img(y,x);
                 method=5;
              end 
          end
      end
      if core_y > 37
         yt=20;
      else
         yt=5;
      end
      test_smooth = 100;
      if core_y > 0
         test_smooth= sum(sum(o_img(core_y-yt-5:core_y-yt+5,core_x-5:core_x+5)));
      end
      if lc > 0.41 && (test_smooth < 109.5 && method~=2 || test_smooth < 100) %&& min(min(o_img(1:core_y-yt,core_x-10:core_x+10))) < 0.17 
         start_t=0;
         core_val=1/(core_val+1);
      else
         core_x=0;
         core_y=0;
         core_val = 255;
      end
      mask=mask_t; path_len = 45;

% Finding Minutiae --------------------------------------------------------
    if display_flag==1; fprintf('done.\n >>> finding minutiae '); end
    minu_count = 1;
    minutiae(minu_count, :) = [0,0,0,0,0,1];
    min_path_index = [];
    % loop through image and find minutiae, ignore certain pixels for border
    for y=20:size(img,1)-14
        for x=21:size(img,2)-21
            if (thinned(y, x) == 1) % only continue if pixel is white
                % calculate CN from Raymond Thai
                CN = 0; sx=0; sy=0;
                for i = 1:8
                  t1 = p(thinned, x, y, i);
                  t2 = p(thinned, x, y, i+1);
                  CN = CN + abs (t1-t2);
                end   
                CN = CN / 2;
                if ((CN == 1) || (CN == 3)) %&& mask(y,x) > 0
                   skip=0;
                   for i = y-5:y+5
                        for j = x-5:x+5
                          if i>0 && j>0 && mask(i,j) == 0   
                             skip=1;
                          end
                        end
                   end
                   if skip == 1
                      continue;
                   end
                   t_a=[];
                   c = 0;
                   for e=y-1:y+1
                       for f=x-1:x+1
                           c = c + 1;
                           t_a(c) = orient_img_m(e,f);
                       end
                   end 
                   m_o = median(t_a); m_f = 0; 
                   if CN == 3
                      [CN, prog, sx, sy,ang]=test_bifurcation(thinned, x,y, m_o, core_x, core_y);
                      if prog < 3
                         continue
                      end
                      if ang < pi 
                         m_o = mod(m_o+pi,2*pi);
                      end
                   else
                      progress=0;
                      xx=x; yy=y; pao=-1; pos=0;
                      while progress < 15 && xx > 1 && yy > 1 && yy<size(img,1) && xx<size(img,2) && pos > -1
                            pos=-1;
                            for g = 1:8
                                [ta, xa, ya] = p(thinned, xx, yy, g);
                                [tb, xb, yb] = p(thinned, xx, yy, g+1);
                                if (ta > tb)  && pos==-1 && g ~= pao
                                   pos=ta; 
                                   if g < 5
                                      pao = 4 + g;
                                   else
                                      pao = mod(4 + g, 9) + 1;
                                   end
                                   xx=xa; yy=ya;
                                end 
                            end
                            progress=progress+1;
                      end
                      if progress < 10
                         continue
                      end
                      if mod(atan2(y-yy,xx-x), 2*pi) > pi
                         m_o=m_o+pi;
                      end
                   end               
                   minutiae(minu_count, :) = [ x, y, CN, m_o, m_f, 1];
                   min_path_index(minu_count, :) = [sx sy];
                   minu_count = minu_count + 1;
                end
            end % if pixel white
        end % for y
    end % for x

% Filtering False Minutiae ------------------------------------------------
    if display_flag==1; fprintf('done.\n >>> filtering false minutiae '); end
    minu_count = minu_count -1;
    t_minutiae = [];
    t_minu_count = 1;
    t_mpi = [];
    for i=1:minu_count
        X = minutiae(i,1); Y = minutiae(i,2);
        rc=0; 
        for y=max(Y-2,1):min(Y+2, size(binim,1)) 
            if rc > 0
               break
            end
            for x=max(X-2,1):min(X+2, size(binim,2))  
                if mask(y,x) == 0
                   rc = rc + 1;   
                   break
                end
            end
        end
        if rc > 0 
             continue;
        else
            t_minutiae(t_minu_count, :) = minutiae(i, :);
            t_mpi(t_minu_count, :) = min_path_index(i, :);
            t_minu_count = t_minu_count + 1;
        end
    end
    minutiae = t_minutiae;
    min_path_index = t_mpi;
    minu_count = size(minutiae,1);
    t_minu_count = 1; t_minutiae = [];
    dist_m = dist2(minutiae(:,1:2), minutiae(:,1:2));
    dist_test=49;
    for i=1:minu_count
      reject_flag = 0;
      P_x = minutiae(i,1); P_y = minutiae(i,2);
      for j = i + 1 : minu_count
        if dist_m(i,j) <= dist_test
           reject_flag = 1;
        end
      end
      if reject_flag == 0 && mask(P_y, P_x) > 0
         reverse_p = 0;  
         if min_path_index(i,1) == 0
           x = P_x;
           y = P_y; 
         else
           x =  min_path_index(i,1);
           y =  min_path_index(i,2); 
         end
         p1x=P_x; p1y=P_y;
         x1=x; y1=y;
         iter = 0;
         for m=1:path_len
               iter = iter + 1;
               cn = 0;
               for ii = 1:8
                   t1 = p(thinned, x1, y1, ii);
                   t2 = p(thinned, x1, y1, ii+1);
                   cn = cn + abs (t1-t2);
               end
               cn = cn / 2;
               if cn ~= 3 && cn ~= 4 || m == 1
                  for n=1:8
                      if reverse_p == 0 || iter > 1 
                         [ta, xa, ya] = p(thinned, x1, y1, n);
                      else
                         [ta, xa, ya] = p(thinned, x1, y1, 9-n);    
                      end
                      if ta == 1 && (xa ~= p1x || ya ~= p1y) && (xa ~= x || ya ~= y)
                         p1x = x1; p1y = y1;
                         x1 = xa; y1 = ya;
                         break;
                      end
                  end
               end
         end
         t_minutiae(t_minu_count, :) = minutiae(i, :);
         t_minu_count = t_minu_count + 1;
      end
    end
    minutiae = t_minutiae;
    minu_count = t_minu_count-1;
    tmpvec1 = size(img,1).*ones(minu_count,1);    
    tmpvec2 = ones(minu_count,1);                 
    minutiae_for_sc = [minutiae(:,1)/size(img,2) (tmpvec1 - minutiae(:,2) + tmpvec2)/size(img,1)];  
    dist_m = sqrt(dist2(minutiae_for_sc(:,1:2), minutiae_for_sc(:,1:2)));
    for i=1:minu_count
      [d,ind] = sort(dist_m(i,:));
      for j = 1 : minu_count
        if  dist_m(i,ind(j)) == 0
           continue
        end
        theta_t = mod(atan2(minutiae(i,2) - minutiae(ind(j),2), minutiae(i,1) - minutiae(ind(j),1)), 2*pi);
        ridge_count = 0;
        p_y = minutiae(i,2);  p_x = minutiae(i,1); 
        t_x = 0; t_y = 0;
        current=1; radius = 1;
        while p_y ~= minutiae(ind(j),2)
            if thinned(p_y, p_x) > 0  && current == 0 && (t_x ~= p_x || t_y ~= p_y)
               current = 1;
               ridge_count = ridge_count + 1;
            else
                 if thinned(p_y, p_x) == 0
                    current = 0;
                 end
            end    
            t_x = p_x; t_y = p_y;
            p_x = round(minutiae(i,1) - radius*cos(theta_t)); 
            p_y = round(minutiae(i,2) - radius*sin(theta_t));
            radius = radius + 1;
        end
      end
    end
    if core_val < 1
      minutiae(minu_count+1, :) = [core_x, core_y, 5, start_t, 0,1]; 
      minu_count = minu_count + 1;
    end
    if dt1 < 1
       minutiae(minu_count+1, :) = [delta1_x, delta1_y, 7, 0, 1,1];
       minu_count = minu_count + 1;
    end
    if dt2 < 1       
       minutiae(minu_count+1, :) = [delta2_x, delta2_y, 7, 0, 1,1];
       minu_count = minu_count + 1;
    end
    if dt3 < 1       
       minutiae(minu_count+1, :) = [delta3_x, delta3_y, 7, 0, 1,1];
       minu_count = minu_count + 1;
    end

% Return Minutiae ---------------------------------------------------------
    if display_flag == 1
        fprintf('done.\n');
        minutiae_img = uint8(zeros(size(img, 1),size(img, 2), 3));
        for i=1:minu_count 
        x1 = minutiae(i, 1); y1 = minutiae(i, 2);
        if minutiae(i, 3) == 1                      %Termination
           if minutiae(i, 4) > pi
            for k = y1-2: y1 + 2
              for l = x1-2: x1 + 2
                minutiae_img(k, l,:) = [255, 0, 0]; 
              end
            end
           else
            for k = y1-2: y1 + 2
              for l = x1-2: x1 + 2
                minutiae_img(k, l,:) = [205, 100, 100]; 
              end
            end
           end
        elseif minutiae(i, 3) == 2
            for k = y1-2: y1 + 2
              for l = x1-2: x1 + 2
                minutiae_img(k, l,:) = [255, 0, 255];
              end
            end
        elseif minutiae(i, 3) == 3                  %Bifurcation
          if minutiae(i, 4) > pi
            for k = y1-2: y1 + 2
              for l = x1-2: x1 + 2
                minutiae_img(k, l,:) = [0, 0, 255]; 
              end
            end
          else 
            for k = y1-2: y1 + 2
              for l = x1-2: x1 + 2
                minutiae_img(k, l,:) = [255, 0, 255];
              end
            end
          end
        elseif minutiae(i, 3) == 5
            for k = y1-4: y1 + 4
              for l = x1-4: x1 + 4
                minutiae_img(k, l,:) = [0, 255, 0]; 
              end
            end
        elseif minutiae(i, 3) > 5
            for k = y1-2: y1 + 2
              for l = x1-2: x1 + 2
                  minutiae_img(k, l,:) = [128, 128, 0]; % gold for delta
              end
            end
        end   
        end
        combined = uint8(minutiae_img);    
        for x=1:size(binim,2)
        for y=1:size(binim,1)
            if mask(y,x) == 0
                combined(y,x,:) = [0,0,0];
                continue
            end
            if (thinned(y,x)) % binim(y,x))
                combined(y,x,:) = [255,255,255];
            else
                combined(y,x,:) = [0,0,0];
            end % end if
            if ((minutiae_img(y,x,3) ~= 0) || (minutiae_img(y,x,1) ~= 0) ) || (minutiae_img(y,x,2) ~= 0)
                combined(y,x,:) = minutiae_img(y,x,:);
            end
        end % end for y
        end % end for x
        if core_val < 1 && YA > 0
            for k = YA-2: YA + 2
              for l = XA-2: XA + 2
                 combined(k,l,:) = [20, 255, 250];
              end
            end
            for k = YB-2: YB + 2
              for l = XB-2: XB + 2
                 combined(k,l,:) = [20, 255, 250];
              end
            end
        end
        subplot(1,2,1), subimage(img), title('Original image')
        subplot(1,2,2), subimage(combined), title('Minutiae')
    end
    ret=minutiae;
end

[uma maheswari k]

i need output for this code

Answer 1

[Walter Roberson]

Ask the author of the code, Vahid. K. Alilou. Or, Learn MATLAB

You are asking for a detailed explanation of over 550 lines of code, and we have no idea what your programming skill level is. It could take several months to explain it to you in detail. Heck, it could take a couple of years to explain to you in detail.

For warm-up, read the first three volumes of Knuth's The Art of Computer Programming and then get back to us

[Ranjan Kumar]

Its not that I am beginner in coding part, the code starts with image enhancement...few lines of codes

yt=1; xl=1; yb=size(img,2); xr=size(img,1);
    for x=1:55
        if numel(find(img(x,:)<200)) < 8
           img(1:x,:) = 255;
           yt=x;
        end
    end
    for x=225:size(img,1)
        if numel(find(img(x,:)<200)) < 3
           img(x-17:size(img,1),:) = 255;
           yb=x;
           break
        end
    end
    for y=200:size(img,2)
        if numel(find(img(:,y)<200)) < 1
           img(:,y:size(img,2)) = 255;
           xr=y;
           break
        end
    end
    for y=1:75
        if numel(find(img(:,y)<200)) < 1
           img(:,1:y) = 255;
           xl=y;
        end  
    end

I am not able to understand the use of this part of code, can u plz explain me the purpose of it

Just give me the hint I will be able to understand.

[Walter Roberson]

I could explain what each line does, but for information about why it is being used, you need to ask the author of the code.

In the original code, the comments give the author's name, and give the reference to a particular paper. The paper might have clues as to what is being done.

[Ranjan Kumar]

Ok pls explain what those lines does

[VYSHAKH V NAIR]

haloo friend i know my reply is too late. am sending this reply just for my sake. i gusse this code is of fingerprint recognition. yb here gives tonal no of column and xr gives total no of rows. here there are 4 for loop using which we asign value 255 to each row and column as per the condetion. i think this is done just to extract the fingerprint region from the whole of the image.

Answer 2

[sana tayeb]

Hello,

I'm working on the same project and I have some question about it.

Could you help, please?