- Loop through images and plot histograms: Ensure that you are plotting the histogram for the first and the last images correctly.
- Clear previous figures: Use 'clf' to clear the current figure before plotting new images and histograms.
- Figure and subplot management: Make sure you create a new figure for each set of subplots to avoid overwriting.
Plot histogram of a series of images and extract cracks
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Elisa
el 17 de Jul. de 2024 a las 12:37
Comentada: Elisa
el 18 de Jul. de 2024 a las 9:32
Dear all,
I'm trying to plot histogram of a series of tomography images to assess the threshold for extracting cracks. I don't understand why the histogram is not displayed. I would like to select at least the first and the last images to determine the threshold. Here is the code:
Thanks a lot for any help
clear all
close all
clc
a= load('tomo_carota_8bit.mat')
x=a.x_8;
x=double(x);
% clear a
%%
figure,
for ii = 1:size(x, 3)
ii
I = squeeze(x(:,:,ii));
imshow(I, []);
pause(0.1)
end
subplot(3,2,1);
imshow(I,[]);
title('Original Grayscale Image', 'FontSize', 15);
subplot(3,2,2);
imhist(I);
title('Histogram of original image');
subplot(3,2,3);
imhist(I);
[counts, grayLevels] = imhist(I);
bar(grayLevels, counts, 'EdgeColor', 'r', 'FaceColor', 'b', 'BarWidth', 1);
xlim([0, max(I(:))]);
%xlim([0 100])
title('Histogram of original image zoomed');
subplot(3,2,4);
thresholdValue = 85;
thresholdValue1 = 60;
f.InvertHardcopy = 'off';
binaryImage1 = I > thresholdValue1;
imshow(binaryImage1, []);
title('Binary Image threshold 85');
f.InvertHardcopy = 'off';
binaryImage = I > thresholdValue;
subplot(3,2,5);
imshow(binaryImage, []);
title('Binary Image threshold 60');
figure (1)
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Respuesta aceptada
Ruchika Parag
el 17 de Jul. de 2024 a las 13:10
Hi Elisa, it looks like you have a few issues in your code that might be causing the histogram not to be displayed properly. Here are some suggestions and corrections to help you plot the histogram of a series of tomography images effectively:
Here is a modified version of your code:
clear all
close all
clc
a = load('tomo_carota_8bit.mat');
x = a.x_8;
x = double(x);
figure,
for ii = 1:size(x, 3)
I = squeeze(x(:, :, ii));
imshow(I, []);
pause(0.1)
end
figure;
I_first = squeeze(x(:, :, 1));
subplot(3, 2, 1);
imshow(I_first, []);
title('First Grayscale Image', 'FontSize', 15);
subplot(3, 2, 2);
imhist(I_first);
title('Histogram of first image');
subplot(3, 2, 3);
[counts, grayLevels] = imhist(I_first);
bar(grayLevels, counts, 'EdgeColor', 'r', 'FaceColor', 'b', 'BarWidth', 1);
xlim([0, max(I_first(:))]);
title('Histogram of first image zoomed');
I_last = squeeze(x(:, :, end));
subplot(3, 2, 4);
imshow(I_last, []);
title('Last Grayscale Image', 'FontSize', 15);
subplot(3, 2, 5);
imhist(I_last);
title('Histogram of last image');
subplot(3, 2, 6);
[counts, grayLevels] = imhist(I_last);
bar(grayLevels, counts, 'EdgeColor', 'r', 'FaceColor', 'b', 'BarWidth', 1);
xlim([0, max(I_last(:))]);
title('Histogram of last image zoomed');
thresholdValue1 = 60;
thresholdValue2 = 85;
figure;
binaryImage1 = I_first > thresholdValue1;
subplot(2, 2, 1);
imshow(binaryImage1, []);
title('Binary Image threshold 60 (First Image)');
binaryImage2 = I_first > thresholdValue2;
subplot(2, 2, 2);
imshow(binaryImage2, []);
title('Binary Image threshold 85 (First Image)');
binaryImage3 = I_last > thresholdValue1;
subplot(2, 2, 3);
imshow(binaryImage3, []);
title('Binary Image threshold 60 (Last Image)');
binaryImage4 = I_last > thresholdValue2;
subplot(2, 2, 4);
imshow(binaryImage4, []);
title('Binary Image threshold 85 (Last Image)');
By making these changes, you should be able to visualize the histograms of the first and last tomography images and determine the appropriate threshold for extracting cracks.
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