Plot histogram of a series of images and extract cracks

Question

Elisa 2024-7-17

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2138057-plot-histogram-of-a-series-of-images-and-extract-cracks

评论： Elisa 2024-7-18

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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Answer 1

Ruchika Parag 2024-7-17

1
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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2138057-plot-histogram-of-a-series-of-images-and-extract-cracks#answer_1486857

在 MATLAB Online 中打开

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:

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.

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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Elisa 2024-7-18

在 MATLAB Online 中打开

image_1567.png

Dear Ruchika Parag, tahnk you very much for your help!!!!

i modified the code according to your suggestion and i also used a png image cause is more simple to be processed by my computer. Anyway, I tried so set thresholds without having the right final result. I would like to remove the black background at first, an then to extract cracks within the circle. Can you help me finding what is not working properly? I tried with circles2mask using imfindcircle at first, then i also tried to create a mask using a threshold for black pixels. here you can find the modified code:

clear all
close all
clc
A= imread('image_1567.png');
%% method 1
[centers,radii] = imfindcircles(A,[50 100],Sensitivity=0.9); 
mask = circles2mask(centers,radii,size(A));
figure
montage({A,mask})
A(~(A == mask)) = nan
%% method 2
FG = fliplr(imadjust(I,[0.05 1])); 
sout = size(I);
squaresize = [10 10];
xx = mod(0:(sout(2)-1),squaresize(2)*2)<squaresize(2);
yy = mod(0:(sout(1)-1),squaresize(1)*2)<squaresize(1);
BG = im2uint8(0.3 + bsxfun(@xor,xx,yy')*0.4);
mask = FG>10;
outpict = BG;
outpict(mask) = FG(mask);
outpict = uint8(double(FG).*mask + double(BG).*(1-mask));
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(outpict);
[counts, grayLevels] = imhist(outpict);
bar(grayLevels, counts, 'EdgeColor', 'r', 'FaceColor', 'b', 'BarWidth', 1);
xlim([0, max(outpict(:))]);
title('Histogram of output image with threshold 60');
subplot(3,2,4);
thresholdValue1 = 60;
f.InvertHardcopy = 'off';
binaryImage1 = outpict > thresholdValue1;
imshow(binaryImage1, []);
title('Binary Image threshold 60');
f.InvertHardcopy = 'off';
figure (1)