Matlab - Ignoring the background of an image - matlab

Question

I'm working on part of an application where I now need to compare two images together and check how similar they are with one another. This is currently done by converting the two images into binary, counting the number of black and white pixels, before finally dividing the number of white pixels with the total number of pixels present inside the image.
The problem I am facing now though is the background for the images I am using since it is counting towards the 'similarity score' and making it an inaccurate result. I have an idea on how to resolve this issue, I just don't know how to put into practice.
For example, say this was the image file and it's pixel values.
0000000000
0000110000
0001001000
0011001100
0001001000
0000110000
0000000000
My idea is to search each row and column from left to right, right to left, up to down and down to up, to detect the number of the black pixels contained in the background of the image. Then hopefully once it detects a white pixel, it stops searching that row/column and moves onto the next. Then finally, when the search is completed, I will know how many black pixels the background takes up and I can then subtract that value away from my grand total, which will the allow me to have a more accurate reading.
I just don't know how to search in this way and I don't want to eliminate every black pixel on screen as they are important because they are also contained inside these objects (example below). Does anybody know how I'd go about doing it this way, or knows an even simpler way?
Current Code:
for i = 1:length(jpgFiles)
baseFileName = jpgFiles(i).name;
fullFileName = fullfile(referenceFolder, baseFileName);
%Reading in the images & converting the images to Black & White
a = im2bw(imread(firstImage));
b = im2bw(imread(fullFileName));
compiledImage = a==b;
fprintf(1, 'Reading %s\n', fullFileName);
axes(handles.axes4);
disp(compiledImage); %Displays the values if the pixels match
[X, Y] = find(a ~= b); %Find coordinates for which the two images are equal
imshow(a); %Show first image
hold on %Retains the current plot and certain axes properties
plot(Y, X, 'y.'); %Overlay those coordinates
hold off %Resets axes properties to their default before drawing new plots
%Getting the values of white and black pixels
blackCount = sum(sum(a==b ==0));
whiteCount = sum(sum(a==b));
disp('Black Count:');
disp(blackCount);
disp('White Count:');
disp(whiteCount);
%Calculating the percentage
maxTotal = blackCount + whiteCount;
decimalValue = whiteCount / maxTotal;
percentageValue = sprintf('%.0f%%',100*decimalValue);
disp(decimalValue);
disp(percentageValue);
%Title settings and delay, if needed
title('Strongest Features (Yellow Hides Any Discrepancies)', 'fontweight', 'bold'); %Sets the title
drawnow;
%pause(5);
%Adding into the image array
imageArray{j} = baseFileName;
j = j + 1;
%Adding into the popular features array
popFeaturesArray{i} = 100*decimalValue;
i = i + 1;
end
Image Examples:

Answer 1

you can do that with some morphological operations:
c1 = rgb2gray(imread('c1.png'));
bw = imfill(imclose(c1 ~= 0,ones(3)),'holes');
bw = bwareafilt(bw,2);
% plotting
A = imoverlay(bw,(c1 > 0).*bw,'b');
imshow(A)
bw is the foreground here.
Edit - if you don't have bwareafilt you can do instead:
n = 2; % keep the two largest areas
cc = bwconncomp(bw);
pixels = cc.PixelIdxList;
sizes = cellfun(#numel,pixels);
[~,idxs] = sort(sizes,'descend');
pixels = cell2mat(pixels(idxs(1:min(n,end)))');
bw(:) = false;
bw(pixels) = true;