How to calculate every peak in plot

How to total every peak in this plot?

This is my code:

fabric_image = imread('Kain1.png'); % Replace 'fabric_image.jpg' with the actual path to your fabric image

gray_fabric = rgb2gray(fabric_image);

threshold = graythresh(gray_fabric);

binary_fabric = imbinarize(gray_fabric, threshold);

horizontal_profile = mean(binary_fabric, 2);

vertical_profile = mean(binary_fabric, 1);

figure;

subplot(2, 1, 1);

plot(horizontal_profile, 'k');

xlabel('Distance Pixel');

ylabel('Average Intensity');

title('Profile Warp');

subplot(2, 1, 2);

plot(vertical_profile, 'k');

xlabel('Distance Pixel');

ylabel('Average Intensity');

title('Profile Weft');

i want to calculate every peak of that every intensity

[pizzaa]

THIS IS THE PLOT

[Image Analyst]

Knowing the peak location of those profiles won't provide you with any useful information because your view of the fabric is oblique. Using findpeaks will be a lesson in failure.

Answer 1

[Animesh]

Hey @pizzaa

To calculate the peaks in the intensity profiles, you can use the findpeaks function in MATLAB. This function finds local maxima in a given vector. Here's how you can modify your code to calculate the peaks:

fabric_image = imread('Kain1.png');
gray_fabric = rgb2gray(fabric_image);
threshold = graythresh(gray_fabric);
binary_fabric = imbinarize(gray_fabric, threshold);
horizontal_profile = mean(binary_fabric, 2);
vertical_profile = mean(binary_fabric, 1);

% Calculate peaks in the horizontal profile
[horizontal_peaks, horizontal_locations] = findpeaks(horizontal_profile);

% Calculate peaks in the vertical profile
[vertical_peaks, vertical_locations] = findpeaks(vertical_profile);

% Plot the profiles with peaks
figure;
subplot(2, 1, 1);
plot(horizontal_profile, 'k');
hold on;
plot(horizontal_locations, horizontal_peaks, 'ro');
xlabel('Distance Pixel');
ylabel('Average Intensity');
title('Profile Warp');
legend('Horizontal Profile', 'Peaks');
hold off;

subplot(2, 1, 2);
plot(vertical_profile, 'k');
hold on;
plot(vertical_locations, vertical_peaks, 'ro');
xlabel('Distance Pixel');
ylabel('Average Intensity');
title('Profile Weft');
legend('Vertical Profile', 'Peaks');
hold off;

This code calculates the peaks in both the horizontal and vertical intensity profiles and plots the profiles with the identified peaks marked as red circles.

You can refer the following documentation for more details:

findpeaks : https://www.mathworks.com/help/signal/ref/findpeaks.html

Answer 2

[Star Strider]

Peak locations, full-width-half-maximum, and areas —

fabric_image = imread('Kain1.png'); % Replace 'fabric_image.jpg' with the actual path to your fabric image
gray_fabric = rgb2gray(fabric_image);
threshold = graythresh(gray_fabric);
binary_fabric = imbinarize(gray_fabric, threshold);
horizontal_profile = mean(binary_fabric, 2);
vertical_profile = mean(binary_fabric, 1);
figure;
subplot(2, 1, 1);
plot(horizontal_profile, 'k');
xlabel('Distance Pixel');
ylabel('Average Intensity');
title('Profile Warp');
subplot(2, 1, 2);
plot(vertical_profile, 'k');
xlabel('Distance Pixel');
ylabel('Average Intensity');
title('Profile Weft');

hidx = horizontal_profile < 1;
hy = horizontal_profile(hidx);
hy = sgolayfilt(hy, 3, 5);
hx = (0 : nnz(hidx)-1).';

vidx = vertical_profile < 1;
vy = vertical_profile(vidx).';
vy = sgolayfilt(vy, 3, 5);
vx = (0 : nnz(vidx)-1).';

hv = {[hx hy], [vx vy]};

ttl = {'Horizontal Profile'; 'Vertical Profile'};

figure
tiledlayout(2,1)
for k1 = 1:numel(hv)
    nexttile
    x = hv{k1}(:,1);
    y = hv{k1}(:,2);
    [pks, plocs] = findpeaks(y);
    plot(x, y)
    hold on
    plot(x(plocs), pks, 'sr')
    hold off
    grid
    title(ttl{k1})
end

for k1 = 1:numel(hv)
    x = hv{k1}(:,1);
    y = hv{k1}(:,2);
    [pks, plocs] = findpeaks(y);
    [vys, vlocs] = findpeaks(-y);
    vys = [vys; y(end)];
    vlocs = [vlocs; numel(x)];
    for k = 1:numel(pks)
        % k
        % Q0 = [vlocs(k) vlocs(k+1)]
        idxrng = vlocs(k) : vlocs(k+1);
        baseline = [x(idxrng) ones(size(x(idxrng)))] * ([x(idxrng([1 end])) ones(2,1)] \ y(idxrng([1 end])));
        idx = ismember(plocs, idxrng);
        if nnz(idx) < 1
            break
        end
        pkidx(k,:) = plocs(idx);
        xpk(k,:) = x(pkidx(k,:));
        ypk(k,:) = y(pkidx(k,:));
        ixvr = vlocs(k) : pkidx(k,:);
        hwv(1,k) = median(y(ixvr([1 end])));
        hw(1,k) = interp1(y(ixvr), x(ixvr), hwv(1,k));
        ixvf = pkidx(k,:) : vlocs(k+1);
        hwv(2,k) = median(y(ixvf([1 end])));
        hw(2,k) = interp1(y(ixvf), x(ixvf), hwv(2,k));
        auc(k,:) = trapz(x(idxrng), y(idxrng)-baseline);
    end
    fwhm = diff(hw).';
    Results = table(table(xpk, ypk, fwhm, auc, 'VariableNames',{'Peak X','Peak Y','FWHM','AUC'}), 'VariableNames',ttl(k1))
end

Results = 46×1 table
               Horizontal Profile           
    Peak X    Peak Y      FWHM        AUC   
    ________________________________________

       7      0.53918    5.9165      0.72751
      20       0.4738    7.9264      0.55584
      34      0.48441    6.1844      0.55624
      47      0.47743    7.2204      0.57743
      60      0.53571    6.1809      0.61367
      65      0.46008         1    0.0021224
      72      0.54747    6.6988       0.5129
      85      0.56971    5.4371      0.52684
      92      0.47065         1    0.0029184
      97      0.52065    7.2364      0.36265
     109      0.50735    5.2293      0.27816
     119      0.44188    1.8226     0.010449
     123      0.47702    5.6774      0.24514
     131      0.42608         1    0.0047347
     134      0.43486    2.9299     0.047265
     141      0.42061    1.9692     0.036939

Results = 66×1 table
                Vertical Profile             
    Peak X    Peak Y      FWHM        AUC    
    _________________________________________

      10      0.45246    6.0789       0.28003
      21      0.43434    2.6445      0.051755
      35      0.45366    10.361       0.28996
      42      0.42786         1      0.001932
      44      0.42819         1    0.00081633
      49      0.45317    5.6125       0.13981
      59      0.44822    2.0512     0.0028844
      63      0.46444    2.5559      0.030857
      68      0.45693    4.9749      0.056109
      77      0.42661      2.91      0.008381
      86        0.416    1.6064     0.0039184
      91      0.43254    4.7985      0.091265
     102      0.45518    2.7289     0.0096327
     106        0.464    2.8341      0.034503
     111      0.45045    1.0714     0.0019592
     118      0.46487    7.3131       0.16648

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