Why I can,t able to use parfor ?-Error: The variable options in a parfor cannot be classified.

I am using parfor since my code takes too much time to compute the features, I here attach the code that i used

      parfor no=1:49
  %      no=num_Frames(nx);
        FEAT=[];
         Org_class=[];
  Ids=[];
  % if sum(ismember(GT_ID,no))
  %     continue;
  % end
  fstr=['D:\My Work\Main Project\OCT\Denoised_cyst\spectralis_',num2str(mac_id),'\bscan_',num2str(no),'.jpg'];
  %fstr=['F:\Anima\M Tech pgm\Main project\OCT cyst segmentation\OCT\Denoised_cyst\spectralis_',num2str(mac_id),'\bscan_',num2str(no),'.jpg'];

% warning('off'); 
 rows=find(file(:,3)==no);
index=[];
for i=1:size(rows,1)
index(i,1)=file(rows(i),1);
index(i,2)=file(rows(i),2);
end
img=imread(fstr);
H = size(img,1);
W = size(img,2);

ibgt1=img;
% ROI restriction removing detected cysts below and above RPE & NFL
%file orders  
idx=find(xid1==no); 
%%creating GT image

grader_M=false(H,W);
 for Row=1:size(index,1)
          grader_M(index(Row,1), index(Row,2)) = true;
 end 
%%Preprocessing
%%Intensity Normalization

originalMinValue = double(min(min(img)));
originalMaxValue = double(max(max(img)));
originalRange = originalMaxValue - originalMinValue;

   % Get a double image in the range 0 to +255
    desiredMinVal = 0;
    desiredMaxVal = 255;
    desiredRange = desiredMaxVal - desiredMinVal;
    dblImageS255 = desiredRange * (double(img) - originalMinValue) /(originalRange + desiredMinVal);

% Get a double image in the range 0 to +1
 desiredMinVal = 0;
 desiredMaxVal = 1;
 desiredRange = desiredMaxVal - desiredMinVal;
 I_norm = desiredRange * (double(img) - originalMinValue) /(originalRange + desiredMinVal);
 %I_Smooth=imgaussfilt(I_norm);
Mask=fspecial('gaussian',[5 5]);
I_Smooth=imfilter(I_norm,Mask,'symmetric');

%%Feature Vector Calculation

           I1=I_Smooth;
           D=strel('Disk',5);
           %I2=mmclose(I_Smooth,mmsedisk(5));
           I2=imclose(I_Smooth,D);
           Mask3=fspecial('gaussian',[5 5],2);
           I3=imfilter(I_norm,Mask3,'symmetric');
           Mask4=fspecial('gaussian',[5 5],4);
           I4=imfilter(I_norm,Mask4,'symmetric');
           Mask5=fspecial('gaussian',[5 5],6);
           I5=imfilter(I_norm,Mask5,'symmetric');
           Mask6=fspecial('gaussian',[5 5],8);
           I6=imfilter(I_norm,Mask6,'symmetric');
           Mask7=fspecial('gaussian',[5 5],10);
           I7=imfilter(I_norm,Mask7,'symmetric');
           Mask8=fspecial('gaussian',[5 5],12);
           I8=imfilter(I_norm,Mask8,'symmetric');
           Mask9=fspecial('gaussian',[5 5],14);
           I9=imfilter(I_norm,Mask9,'symmetric');
           Mask10=fspecial('gaussian',[5 5],16);
           I10=imfilter(I_norm,Mask10,'symmetric');
           Mask11=fspecial('gaussian',[5 5],18);
           I11=imfilter(I_norm,Mask11,'symmetric');
           h1=fspecial('laplacian',1);
           I12=imfilter(I_norm,h1);
           h2=fspecial('log',[3 3],2);
           I13=imfilter(I_norm,h2);

           sz=1; %sz>=2 MBLBP
  I_p1 = padarray(I_Smooth, [sz sz], 'replicate');
  [Ny , Nx]         = size(I_p1);
  N                 = 8;
  scale             = sz*[1  ; 1 ];

options.F         = mblbp_featlist(Ny , Nx , scale);
options.map       = uint8(0:2^N-1);
z1                = mblbp(I_p1 , options);

template          = options.F(: , 1);

Nxx               = (Nx-3*template(4) + 1);
Nyy               = (Ny-3*template(5) + 1);

Imblbp1           = reshape(z1 , Nyy , Nxx);

sz1=2; %sz>=2 MBLBP
I_p2 = padarray(I_Smooth, [sz1 sz1], 'replicate');
[Ny1 , Nx1]         = size(I_p2);
N1                = 8;
scale1             = sz1*[1  ; 1 ];

options.F         = mblbp_featlist(Ny1 , Nx1 , scale1);
options.map       = uint8(0:2^N-1);
z12                = mblbp(I_p2 , options);

template1          = options.F(: , 1);

Nxx1               = (Nx1-3*template1(4) + 1);
Nyy1               = (Ny1-3*template1(5) + 1);

Imblbp12           = reshape(z12 , Nyy1 , Nxx1);

   sz2=3; %sz>=2 MBLBP
  I_p3 = padarray(img, [sz2 sz2], 'replicate');
  [Ny2 , Nx2]         = size(I_p3);
  N2                 = 8;
  scale2             = sz2*[1  ; 1 ];

options.F         = mblbp_featlist(Ny2 , Nx2 , scale2);
options.map       = uint8(0:2^N2-1);
z13                = mblbp(I_p3 , options);

template2          = options.F(: , 1);

Nxx2               = (Nx2-3*template2(4) + 1);
Nyy2               = (Ny2-3*template2(5) + 1);

Imblbp13           = reshape(z13 , Nyy2 , Nxx2);

sz3=4; %sz>=2 MBLBP
I_p4 = padarray(I_Smooth, [sz3 sz3], 'replicate');
[Ny3 , Nx3]         = size(I_p4);
N3                 = 8;
scale3             = sz3*[1  ; 1 ];

options.F         = mblbp_featlist(Ny3 , Nx3 , scale3);
options.map       = uint8(0:2^N3-1);
z14                = mblbp(I_p4 , options);

template3          = options.F(: , 1);

Nxx3               = (Nx3-3*template3(4) + 1);
Nyy3               = (Ny3-3*template3(5) + 1);

Imblbp14           = reshape(z14 , Nyy3 , Nxx3);
%%Test data Generation

   [X Y]=size(I_Smooth);
  for inx=10:W-10
  for i=x2(inx,idx):x3(inx,idx) %NFL to RPE
  % for inx=2:X-10
  % for i=2:Y-10    
      win=I_Smooth(i-1:i+1,inx-1:inx+1);
                I_ta=win;
                Contrast1=[];
                Homog1=[];
                Energy1=[];
                Corr1=[];
                glcms1=graycomatrix(win,'Offset',[-1 -1;0 0; 0 -1; -1 1]);
                stats1=graycoprops(glcms1);

                Contrast1=[Contrast1;stats1.Contrast];
                Homog1=[Homog1;stats1.Homogeneity];
                Energy1=[Energy1;stats1.Energy];
                Corr1=[Corr1;stats1.Correlation];

                        I1=double(I1);
                        I2=double(I2);
                        I3=double(I3);
                        I4=double(I4);
                        I5=double(I5);
                        I6=double(I6);
                        I7=double(I7);
                        I8=double(I8);
                        I9=double(I9);
                       I10=double(I10);
                       I11=double(I11);
                       I12=double(I12);
                       I13=double(I13);
                       Imblbp1=double(Imblbp1);
                       Imblbp12=double(Imblbp12);
                       Imblbp13=double(Imblbp13); 
                       Imblbp14=double(Imblbp14); 
                       Contrast1=double(Contrast1);
                       Homog1=double( Homog1);
                       Energy1=double( Energy1);
                       Corr1=double( Corr1);

            if grader_M(i,inx)==1

                         FEAT=[ FEAT;I1(i,inx), I2(i,inx),I3(i,inx),I4(i,inx),I5(i,inx),I6(i,inx),I7(i,inx),I8(i,inx),I9(i,inx),I10(i,inx),I11(i,inx),I12(i,inx),I13(i,inx),Imblbp1(i,inx),Imblbp12(i,inx),Imblbp13(i,inx),Imblbp14(i,inx),Contrast1, Homog1,Energy1,Corr1]; 
                        Ids=[Ids;mac_id,no,i,inx];
                        Org_class=[Org_class;1];
            else
                FEAT=[ FEAT;I1(i,inx), I2(i,inx),I3(i,inx),I4(i,inx),I5(i,inx),I6(i,inx),I7(i,inx),I8(i,inx),I9(i,inx),I10(i,inx),I11(i,inx),I12(i,inx),I13(i,inx),Imblbp1(i,inx),Imblbp12(i,inx),Imblbp13(i,inx),Imblbp14(i,inx),Contrast1, Homog1,Energy1,Corr1]; 
                        Ids=[Ids;mac_id,no,i,inx];
                        Org_class=[Org_class;0];
            end
       end
  end

Answer 1

[Walter Roberson]

Did you define "options" before the parfor? If you did then parfor is going to see the code as trying to update "options". Any temporary variable of the computation should not be initialized before the "parfor" loop.

[Anima V A]

I define the fields before par for