why accuracy is same for all the frames?

clc
close all
clear all
a=VideoReader('G:\New Folder (2)\test1.mp4');                                   % Read a video
b = read(a,1);                                               % Read 1st frame
c=rgb2gray(b);                                               % Converting from RGB to GRAY 
rows = 8;
columns = 8;
nframe=a.NumberOfFrames;                                     % Number of Frames in video read
tic
for i=100:117
    d =read(a,i-1);                                          % Read Previous frame
    e1=rgb2gray(d);
    e=immultiply(e1,2);
g =read(a,i);                                            % Read Current frame
    f1=rgb2gray(g);
    f = immultiply(f1,2);
res = f-e;
    res_bw = im2bw(res);
%     figure
%     imshow(res_bw)
%     title('reference image');
    [HH,WW,~] = size(res_bw);                        % H=Rows  W=Columns
    szHH = [repmat(fix(HH/rows),1,rows)];       % Splitting the original size of an image  into 8X8 cells in rows
    szWW = [repmat(fix(WW/columns),1,columns)]; % Splitting the original size of an image  into 8X8 cells in columns
    CC = mat2cell(res_bw, szHH, szWW)';               % Segmenting the image e into 8X8 cell
    figure
    for jj=1:rows*columns
        subplot(rows,columns,jj), imshow( CC{jj} )
    end
    img=getframe(gcf);
   imwrite(img.cdata,['E:\frame\reference_image.png'])
   [H,W,~] = size(e);                        % H=Rows  W=Columns
    szH = [repmat(fix(H/rows),1,rows)];       % Splitting the original size of an image  into 8X8 cells in rows
    szW = [repmat(fix(W/columns),1,columns)]; % Splitting the original size of an image  into 8X8 cells in columns
    C = mat2cell(e, szH, szW)';               % Segmenting the image e into 8X8 cells
    D =mat2cell(f, szH, szW)';                % Segmenting the image f into 8X8 cells
    C1 = C';
    D1 = D';
%     figure
%     for j=1:rows*columns
%         subplot(rows,columns,j), imshow( C{j} )
%     end
%     figure
  %     for j=1:rows*columns
  %         subplot(rows,columns,j), imshow( D{j} )
  %     end
  %     figure
      for k=1:64
          E1={C{k}};
          E{k}=cell2mat(E1);
          subplot(rows,columns,k), imshow( E{k} )
      end
  %     figure
      for k=1:64
          F1={D{k}};
          F{k}=cell2mat(F1);
          subplot(rows,columns,k), imshow( F{k} )
      end
  %     figure
      for r=1:64
          w(r)=abs(std2(double(E{r})));                  % computes the standard deviation of the values in E
  %         figure
  %         plot(w);
          ceil(w);
          q(r)=abs(std2(double(F{r})));                  % computes the standard deviation of the values in F
  %         figure
  %         plot(q);
          ceil(q);
          diff=w-q;
          level(r) = graythresh(E{r}) ;              % determine Otsu Threshold value
          level1(r) = graythresh(F{r});
            if  diff(r)>level(r)
            T=im2bw(E{r});
            subplot(rows,columns,r);
            imshow(T)
               elseif diff(r)<level(r)
              T1 = im2bw(E{r});
              T1=0;
              subplot(rows,columns,r);
              imshow(T1)
               elseif diff(r)<level1(r)
              P=im2bw(F{r});
              imshow(P)
              elseif diff(r)>level1(r)
              P1 = im2bw(F{r});
              P1=0;
              subplot(rows,columns,r)
              imshow(P1)
               end
                img=getframe(gcf);
          imwrite(img.cdata,['E:\frame\output.png']);
      end  
       TargetImg=imread('E:\frame\reference_image.png');
      TestImg=imread('E:\frame\output.png');
    TargetMask = zeros(size(TargetImg));
    TargetMask= TargetImg>0;
    NotTargetMask = logical(1-TargetMask);
    TestMask = zeros(size(TestImg));
    TestMask= TestImg>0;
    FPimg = TestMask.*NotTargetMask;
    FPcounts = sum(FPimg);
    FP = sum(FPimg(:));
    TPimg = TestMask.*TargetMask;
    TPcounts = sum(TPimg);
    TP = sum(TPimg(:));
    FNimg = TargetMask-TPimg;
    FNcounts = sum(FNimg);
    FN = sum(FNimg(:));
    TNimg = 1- FPimg;
    TNcounts = sum(TNimg);
    TN =sum(TNimg(:));
    accuracy(i)=(((TP+TN)/(TP+TN+FN+FP))*100);
    Sensitivity(i)= TP/(TP+FN)*100 ;
    Specificity(i)= TN/(TN+FP)*100 ;
    end
    xlabel1=100:1:117;
    ylabel1=accuracy(100:117);
    figure
    plot(xlabel1,ylabel1)
    xlabel('frames per second')
    ylabel('Accuracy')
    title('Accuracy')
     how to vary accuracy what changes i should make?