How to solve Index exceeds matrix dimensions problem?

The error 'Index exceeds matrix dimensions' in A New Fast And Efficient Hmm based Face Recognition system using a 7 state hmm along with SVD Coefficients i done my coding in 2017a Matlab version please rectify my error. Many days i searching the solution i didn't get that.

[Walter Roberson]

You have not shown us your code or shown us the line that has the error.

[sruthi N]

sorry Sir

    if (exist('DATABASE.mat','file'))
      load DATABASE.mat;
  end
  while (1==1)
      choice=menu('Face Recognition',...
                  'Generate Database',...
                  'Calculate Recognition Rate',...
                  'Recognize from Image',...
                  'Contents of Folder',...
                  'Result Comparison',...
                  'Exit');
      if (choice ==1)
          if (~exist('DATABASE.mat','file'))
              [myDatabase,minmax] = gendata();        
          else
              pause(0.1);    
              choice2 = questdlg('Generating a new database will remove any previous trained database. Are you sure?', ...
                                 'Warning...',...
                                 'Yes', ...
                                 'No','No');            
              switch choice2
                  case 'Yes'
                      pause(0.1);
                      [myDatabase,minmax] = gendata();        
                  case 'No'
              end
          end        
      end
      if (choice == 2)
          if (~exist('myDatabase','var'))
              fprintf('Please generate database first!\n');
          else
              recognition_rate = testsys(myDatabase,minmax);                
          end                        
      end    
      if (choice == 3)

          if (~exist('myDatabase','var'))

              fprintf('Please generate database first!\n');

          else            
              pause(0.1);            
              [file_name file_path] = uigetfile ({'*.pgm';'*.jpg';'*.png'});
              if file_path ~= 0
                  filename = [file_path,file_name];                
                  facerec (filename,myDatabase,minmax);                        
              end
          end
      end

     if(choice == 4)

         prompt='Please enter Folder No(From 1 to 40):';
  z=input(prompt);
   a=('./data/s')
    z=num2str(z);
    z1=strcat(a,z);
    dir(z1)
  for (i=1:1:10)

      i=num2str(i);
      a11='/';
      a11=strcat(a11,i);
      a1='.pgm';
      a2=strcat(a11,a1);
      a3=strcat(z1,a2);
      figure
      subplot(1,2,1), imshow(a3)

      pause(1)

end
   end
   if (choice == 5)
       d1= [96.5,87.5];
       bar(d1,0.2)
       legend('1-Proposed','2-Existing')
   end

      if (choice == 6)
          clear choice choice2
          return;
      end    
  end

ERROR

Loading Faces ...
Index exceeds matrix dimensions.

Error in gendata (line 51)
            blk_coeffs = myDatabase{1,person_index}{block_index,image_index};

Error in mainmenu (line 30)
                    [myDatabase,minmax] = gendata();

[Walter Roberson]

You did not show the source for gendata

[sruthi N]

Function of the Gendata

function [myDatabase,minmax] = gendata()

eps=.000001;
ufft = [1 5 6 8 10];
fprintf ('Loading Faces ...\n');
data_folder_contents = dir ('./data');
myDatabase = cell(0,0);
person_index = 0;
max_coeffs = [-Inf -Inf -Inf];
min_coeffs = [ Inf  0  0];
for person=1:size(data_folder_contents,1);
    if (strcmp(data_folder_contents(person,1).name,'.') || ...
        strcmp(data_folder_contents(person,1).name,'..') || ...
        (data_folder_contents(person,1).isdir == 0))
        continue;
    end
    person_index = person_index+1;
    person_name = data_folder_contents(person,1).name;
    myDatabase{1,person_index} = person_name;
    fprintf([person_name,' ']);
    person_folder_contents = dir(['./data/',person_name,'/*.pgm']);    
    blk_cell = cell(0,0);
    for face_index=1:5
        I = imread(['./data/',person_name,'/',person_folder_contents(ufft(face_index),1).name]);
        I = imresize(I,[56 46]);
        I = ordfilt2(I,1,true(3));        
        blk_index = 0;
        for blk_begin=1:52
            blk_index=blk_index+1;
            blk = I(blk_begin:blk_begin+4,:);            
            [U,S,V] = svd(double(blk));
            blk_coeffs = [U(1,1) S(1,1) S(2,2)];
            max_coeffs = max([max_coeffs;blk_coeffs]);
            min_coeffs = min([min_coeffs;blk_coeffs]);
            blk_cell{blk_index,face_index} = blk_coeffs;
        end
    end
    myDatabase{2,person_index} = blk_cell;
    if (mod(person_index,10)==0)
        fprintf('\n');
    end
end
delta = (max_coeffs-min_coeffs)./([18 10 7]-eps);
minmax = [min_coeffs;max_coeffs;delta];
for person_index=1:40
    for image_index=1:5
        for block_index=1:52
            blk_coeffs = myDatabase{2,person_index}{block_index,image_index};
            min_coeffs = minmax(1,:);
            delta_coeffs = minmax(3,:);
            qt = floor((blk_coeffs-min_coeffs)./delta_coeffs);
            myDatabase{3,person_index}{block_index,image_index} = qt;
            label = qt(1)*10*7+qt(2)*7+qt(3)+1;            
            myDatabase{4,person_index}{block_index,image_index} = label;
        end
        myDatabase{5,person_index}{1,image_index} = cell2mat(myDatabase{4,person_index}(:,image_index));
    end
end

TRGUESS = ones(7,7) * eps;
TRGUESS(7,7) = 1;
for r=1:6
        TRGUESS(r,r) = 0.6;
        TRGUESS(r,r+1) = 0.4;    
end

EMITGUESS = (1/1260)*ones(7,1260);

fprintf('\nTraining ...\n');
for person_index=1:40
    fprintf([myDatabase{1,person_index},' ']);
    seqmat = cell2mat(myDatabase{5,person_index})';
    [ESTTR,ESTEMIT]=hmmtrain(seqmat,TRGUESS,EMITGUESS,'Tolerance',.01,'Maxiterations',10,'Algorithm', 'BaumWelch');
    ESTTR = max(ESTTR,eps);
    ESTEMIT = max(ESTEMIT,eps);
    myDatabase{6,person_index}{1,1} = ESTTR;
    myDatabase{6,person_index}{1,2} = ESTEMIT;
    if (mod(person_index,10)==0)
        fprintf('\n');
    end
end
fprintf('done.\n');
save DATABASE myDatabase minmax

I have attached my database

[Walter Roberson]

The error message that you posted is for a line of code that does not exist in this file, as it refers to myDatabase{1,person_index} in a line of code that in the source posted uses myDatabase{2,person_index}

The error trace that you posted would occur if

data_folder_contents = dir ('./data');

returned only the folders '.' and '..' and no other folders.

Answer 1

[sruthi N]

function for gendata

function [myDatabase,minmax] = gendata()

eps=.000001;
ufft = [1 5 6 8 10];
fprintf ('Loading Faces ...\n');
data_folder_contents = dir ('./data');
myDatabase = cell(0,0);
person_index = 0;
max_coeffs = [-Inf -Inf -Inf];
min_coeffs = [ Inf  0  0];
for person=1:size(data_folder_contents,1);
    if (strcmp(data_folder_contents(person,1).name,'.') || ...
        strcmp(data_folder_contents(person,1).name,'..') || ...
        (data_folder_contents(person,1).isdir == 0))
        continue;
    end
    person_index = person_index+1;
    person_name = data_folder_contents(person,1).name;
    myDatabase{1,person_index} = person_name;
    fprintf([person_name,' ']);
    person_folder_contents = dir(['./data/',person_name,'/*.pgm']);    
    blk_cell = cell(0,0);
    for face_index=1:5
        I = imread(['./data/',person_name,'/',person_folder_contents(ufft(face_index),1).name]);
        I = imresize(I,[56 46]);
        I = ordfilt2(I,1,true(3));        
        blk_index = 0;
        for blk_begin=1:52
            blk_index=blk_index+1;
            blk = I(blk_begin:blk_begin+4,:);            
            [U,S,V] = svd(double(blk));
            blk_coeffs = [U(1,1) S(1,1) S(2,2)];
            max_coeffs = max([max_coeffs;blk_coeffs]);
            min_coeffs = min([min_coeffs;blk_coeffs]);
            blk_cell{blk_index,face_index} = blk_coeffs;
        end
    end
    myDatabase{2,person_index} = blk_cell;
    if (mod(person_index,10)==0)
        fprintf('\n');
    end
end
delta = (max_coeffs-min_coeffs)./([18 10 7]-eps);
minmax = [min_coeffs;max_coeffs;delta];
for person_index=1:40
    for image_index=1:5
        for block_index=1:52
            blk_coeffs = myDatabase{2,person_index}{block_index,image_index};
            min_coeffs = minmax(1,:);
            delta_coeffs = minmax(3,:);
            qt = floor((blk_coeffs-min_coeffs)./delta_coeffs);
            myDatabase{3,person_index}{block_index,image_index} = qt;
            label = qt(1)*10*7+qt(2)*7+qt(3)+1;            
            myDatabase{4,person_index}{block_index,image_index} = label;
        end
        myDatabase{5,person_index}{1,image_index} = cell2mat(myDatabase{4,person_index}(:,image_index));
    end
end

TRGUESS = ones(7,7) * eps;
TRGUESS(7,7) = 1;
for r=1:6
        TRGUESS(r,r) = 0.6;
        TRGUESS(r,r+1) = 0.4;    
end

EMITGUESS = (1/1260)*ones(7,1260);

fprintf('\nTraining ...\n');
for person_index=1:40
    fprintf([myDatabase{1,person_index},' ']);
    seqmat = cell2mat(myDatabase{5,person_index})';
    [ESTTR,ESTEMIT]=hmmtrain(seqmat,TRGUESS,EMITGUESS,'Tolerance',.01,'Maxiterations',10,'Algorithm', 'BaumWelch');
    ESTTR = max(ESTTR,eps);
    ESTEMIT = max(ESTEMIT,eps);
    myDatabase{6,person_index}{1,1} = ESTTR;
    myDatabase{6,person_index}{1,2} = ESTEMIT;
    if (mod(person_index,10)==0)
        fprintf('\n');
    end
end
fprintf('done.\n');
save DATABASE myDatabase minmax

I have also attached my Database