% Algorithm to find the 2 best matching images within the I images data set
% Attempt to shorten the execution time
function [k] = CompareHistogram(I, maxVal)
progressbar([],0)
tic;
sprintf('Started searching for the 2 best images... (may take a while)')
resultMax = 0;
resultKey = 0;
resultImage = 0;
euclDistance = 0;
maxVal=5;
k = 0;


% Loop through all the data images
for i=1:1:maxVal-1
    A1 = I{i};
    HistA1=imhist(rgb2gray(A1));
    %hn1=imhist(HistA1)./numel(HistA1);

    %Reference image
    % Loop through all the other images (with index higher than i)
    %clearvars cor;
    for j=i+1:1:maxVal
        A2 = I{j}; %Image to compare with the reference image
        HistA2=imhist(rgb2gray(A2));

        euclDistance = euclDistance + pdist2(sum(sum(HistA1)),sum(sum(HistA2)));
        euclDistance

        if j=i+1
            M = euclDistance;
            k = j;
        else if euclDistance < M
            M = euclDistance;
            k = j;
        end
%         progressbar([],j/maxVal);
    end
    M
    if M > resultMax
        resultMax = M;
        resultKey = k;
        resultImage = i;
    end
    progressbar(i/(maxVal-1));
end

sprintf('RESULTAAT: Afbeelding %d matcht het beste met afbeelding %d corr: %s',resultImage,resultKey,num2str(resultMax))
sprintf('Berekening duurde %s seconden',num2str(toc))
%
% figure('position',[200, 50, 600, 600]);
%
% subplot(2,1,1), imshow(I{resultImage});
% subplot(2,1,2), imshow(I{resultKey});