Background Subtraction

%Read Background Image
Background = imread('background.bmp');

%Read Current Frame
CurrentFrame = imread('original.bmp');

%Display Background and Foreground
subplot(2,2,1); imshow(Background); title('BackGround');
subplot(2,2,2); imshow(CurrentFrame); title('Current Frame');

%Convert RGB 2 HSV Color conversion
[Background_hsv]    = round(rgb2hsv(Background));
[CurrentFrame_hsv] = round(rgb2hsv(CurrentFrame));
Out = bitxor(Background_hsv, CurrentFrame_hsv);

%Convert RGB 2 GRAY
Out = rgb2gray(Out);

%Read Rows and Columns of the Image
[rows columns] = size(Out);

%Convert to Binary Image
for i = 1:rows
     for j = 1:columns
         if Out(i, j) > 0
             BinaryImage(i,j) = 1;
         else
             BinaryImage(i,j) = 0;
         end
    end
end

%Apply Median filter to remove Noise
FilteredImage = medfilt2(BinaryImage,[5 5]);

%Boundary Label the Filtered Image
[L num] = bwlabel(FilteredImage);
STATS = regionprops(L, 'all');
cc = [];
removed = 0;

%Remove the noisy regions 
for i=1:num
      dd=STATS(i).Area;

       if (dd < 500)
           L(L==i)=0;
           removed = removed + 1;
           num=num-1;
       else
       end
end

[L2 num2] = bwlabel(L);

% Trace region boundaries in a binary image.
[B,L,N,A] = bwboundaries(L2);

%Display results
subplot(2,2,3), imshow(L2); title('BackGround Detected');
subplot(2,2,4), imshow(L2); title('Blob Detected');

hold on;

for k=1:length(B),
     if(~sum(A(k,:)))
          boundary = B{k};
          plot(boundary(:,2), boundary(:,1), 'r','LineWidth',2);

          for l=find(A(:,k))'
                boundary = B{l};
                plot(boundary(:,2), boundary(:,1), 'g','LineWidth',2);
          end
     end
end

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Refer to https://www.pantechsolutions.net/blog/matlab-code-for-background-subtraction/