Concrete Crack Width Measurement

Question

Ilgin Sandalci 2020-7-12

1
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/563909-concrete-crack-width-measurement

评论： Image Analyst 2024-5-21

B-50X.jpeg

Hi,

I have many images of cracked concrete samples. I have to calculate the average widths of cracks. My supervisor suggested me to use ImageJ for this issue. However I have never used imageJ before. I will be really appreciate if anyone help me and offer me a method and so on. Thanks in advance.

Also I attached the image of cracked concrete sample.

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Walter Roberson 2020-7-13

https://www.mathworks.com/matlabcentral/answers/?term=tag%3A%22crack%22

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Answer 1

Image Analyst 2020-7-13

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/563909-concrete-crack-width-measurement#answer_464897

See my Image Segmentation Tutorial. My File Exchange

What I might do is to use bwskel() to get the length of the crack. Then use regionprops() to get the area. Then divide the two to get the mean width. Also search the forum for cracks - it's been seen here several times before.

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Ilgin Sandalci 2020-7-13

Thanks for your help.

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Answer 2

Image Analyst 2020-7-14

2
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/563909-concrete-crack-width-measurement#answer_465365

在 MATLAB Online 中打开

Ilgin, your last post does not exactly scream "I know I can do this!" So I'm giving you a start with this little snippet:

% Code to detect dark cracks in a concrete image and compute the average width of the cracks.
% By Image Analyst
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
%--------------------------------------------------------------------------------------------------------
%    READ IN IMAGE
folder = pwd;
baseFileName = 'concrete.jpeg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, 'file')
		% Still didn't find it.  Alert user.
		errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
		uiwait(warndlg(errorMessage));
		return;
	end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
% 	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	grayImage = grayImage(:, :, 1); % Take red channel.
end
% Crop it to the right lines.
% grayImage = grayImage(1750:2250, 800:end);
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
title('Red Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Histogram of Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Do a morphological opening filter
se = strel('disk', 9, 0);
filteredImage = imopen(grayImage, se);
subplot(2, 2, 3);
imshow(filteredImage);
impixelinfo;
title('Opened Image', 'FontSize', fontSize, 'Interpreter', 'None');
subplot(2, 2, 2);
imhist(filteredImage);
grid on;
title('Histogram of Morphologically Opened Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image by interactively thresholding using the function at
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image
% 60 seems good for this image.
lowThreshold = 0;
highThreshold = 60;
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, filteredImage)
mask = filteredImage > lowThreshold & filteredImage < highThreshold;
mask = imfill(mask, 'holes');
minAcceptableArea = 10000;
mask = bwareafilt(mask, [minAcceptableArea, inf]);
subplot(2, 2, 4);
imshow(mask, []);
impixelinfo;
caption = sprintf('Binary Image of Cracks larger than %d', minAcceptableArea);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Measure the areas
props = regionprops(mask, 'Area');
allAreas = [props.Area]
out = bwferet(mask)
averageLengths = sort(allAreas ./ out.MaxDiameter, 'descend')
message = sprintf('The average width = %.2f pixels.', averageLengths(1));
fprintf('%s\n', message);
caption = sprintf('Binary Image of Cracks larger than %d\nAverage width of largest = %.2f pixels', minAcceptableArea, averageLengths(1));
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
uiwait(helpdlg(message));

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yasmin ismail 2022-11-7

when i tried these two functions before using bwareafilt and click on run I got like this :

allAreas =

Columns 1 through 7

0 0 0 0 0 0 1

Columns 8 through 14

5 10 9 13 14 43 130

Columns 15 through 21

345 647 623 729 795 922 1010

Columns 22 through 28

1023 1140 1069 1215 1413 2129 5782

Columns 29 through 35

15098 25281 32779 34692 34480 27301 19644

Columns 36 through 42

14152 10536 8292 6419 5051 4379 3350

Columns 43 through 49

2921 2899 2995 2539 2206 1778 1151

Columns 50 through 56

1132 986 805 714 761 533 346

Columns 57 through 63

460 299 349 245 285 208 158

Columns 64 through 70

179 156 154 151 109 99 83

Columns 71 through 77

92 79 79 115 69 86 87

Columns 78 through 84

81 71 76 67 50 68 58

Columns 85 through 91

62 97 35 63 57 74 47

Columns 92 through 98

68 58 61 48 45 58 44

Columns 99 through 105

38 64 59 46 41 48 64

Columns 106 through 112

41 65 45 23 59 33 54

Columns 113 through 119

45 43 48 57 34 66 64

Columns 120 through 126

59 70 50 25 62 71 61

Columns 127 through 133

50 47 53 45 102 62 38

Columns 134 through 140

38 91 55 98 47 97 54

Columns 141 through 147

65 79 51 51 101 60 80

Columns 148 through 154

68 48 70 67 75 74 56

Columns 155 through 161

91 54 61 104 118 53 106

Columns 162 through 168

19 43 64 68 53 32 46

Columns 169 through 175

26 31 35 22 39 17 44

Columns 176 through 182

16 16 15 30 20 24 23

Columns 183 through 189

36 25 18 14 10 16 15

Columns 190 through 196

14 11 28 14 8 10 7

Columns 197 through 203

19 8 17 2 4 16 14

Columns 204 through 210

4 17 7 5 4 5 4

Columns 211 through 217

7 6 2 5 3 2 5

Columns 218 through 220

3 2 1

>>

yasmin ismail 2022-11-9

clc

clear all

fontSize = 10;

I=imread('crack2.jpg');

II=rgb2gray(I);

I2 = II(1:640,350:end);

subplot(2,2,1);imshow(I2);title('Original Image');

subplot(2,2,2);histogram(I2);title('histogram Gray image');

III=I2>90;

mask = imfill(III, 'holes');

Bw=imcomplement(mask);

se=strel('sphere',2);

filteredImage = imopen(Bw,se);

subplot(2, 2, 3);imshow(filteredImage);title('Opened Image');

minAcceptableArea =10000;

mask = bwareafilt(filteredImage,[minAcceptableArea]);

subplot(2, 2, 4);imshow(mask);

props = regionprops(mask, 'Area');

allAreas = [props.Area];

out = bwferet(mask);

averageLengths = sort(allAreas / out.MaxDiameter, 'descend');

message = sprintf('The average width = %.2f pixels.', averageLengths(1));

fprintf('%s\n', message);

caption = sprintf('Binary Image of Cracks larger than %d\nAverage width of largest = %.2f pixels', minAcceptableArea, averageLengths(1));

title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

uiwait(helpdlg(message));

I attached the image that I used and;

I found the crack area between 10000 and 15000 wich is the less frequency in histogram as I understand, when i put minAcceptablearea=10000 the width not apear, only at 1 but unfortunatley some parts of cracks lost and samething happened with other image I dont know why?

Image Analyst 2022-11-9

在 MATLAB Online 中打开

crack2.jpg

This works fine for this particular image:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 14;
%----------------------------------------------------------------------------
% Read in image and convert to gray scale.
rgbImage = imread('crack2.jpg');
grayImage = rgb2gray(rgbImage);
%----------------------------------------------------------------------------
% Crop image.
I2 = grayImage(1:640, 350:end);
subplot(2,2,1);
imshow(I2);
title('Original Image');
%----------------------------------------------------------------------------
% Take histogram.
subplot(2,2,2);
histogram(I2);
grid on;
title('histogram Gray image');
%----------------------------------------------------------------------------
% Binarize image.
threshold = 90;
xline(threshold, 'Color', 'r', 'LineWidth',2)
mask=I2 < threshold;
mask = imfill(mask, 'holes');
%----------------------------------------------------------------------------
% Filter image.
se=strel('sphere',2);
filteredImage = imopen(mask, se);
subplot(2, 2, 3);
imshow(filteredImage);
title('Opened Image');
minAcceptableArea = 10000;
mask = bwareafilt(filteredImage, [minAcceptableArea, inf]);
subplot(2, 2, 4);
imshow(mask);
%----------------------------------------------------------------------------
% Measure size of crack.
props = regionprops(mask, 'Area');
allAreas = [props.Area];
out = bwferet(mask)
% Get width = area / maximum length
averageWidths = sort(allAreas / out.MaxDiameter, 'descend');
message = sprintf('The average width = %.2f pixels.', averageWidths(1));
fprintf('%s\n', message);
caption = sprintf('Binary Image of Cracks larger than %d\nAverage width of largest = %.2f pixels', minAcceptableArea, averageWidths(1));
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
uiwait(helpdlg(message));

yasmin ismail 2022-11-10

编辑：yasmin ismail 2022-11-10

and can you explain the following

props = regionprops(mask, 'Area'); this one to return area measurment

allAreas = [props.Area]; this one not clear

out = bwferet(mask) this also not clear

Image Analyst 2022-11-10

@yasmin ismail I explained the bwareafilt in my last comment.

bwferet is explained in the help but it is basically the caliper width of blobs.

props is a structure and putting brackets around one of the fields is a shortcut way to extract and concatenate all the structure fields, from each structure in the structure array, into a 1-D list of all the numbers.

regionprops is the main function in the Image Processing Toolbox to make various measurements on the segmented (binary/logical) mask image.

Have you gone through my Image Segmentation Tutorial?

Image Analyst's File Exchange

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Answer 3

yasmin ismail 2023-3-5

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/563909-concrete-crack-width-measurement#answer_1185590

编辑：Image Analyst 2023-3-6

在 MATLAB Online 中打开

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 10;
% Read in image and convert to gray scale.
rgbImage = imread('7002-9.jpg');
I = rgb2gray(rgbImage);
subplot(2,2,1);
imshow(I);
title('7001-21');
% Take histogram.
subplot(2,2,2);
histogram(I);
grid on;  %to make grid line
title('histogram Gray image');
% Binarize image.
threshold = 145;
xline(threshold, 'Color', 'r', 'LineWidth',2)
mask=I < threshold;
mask = imfill(mask, 'holes');
% Filter image.
se=strel('sphere',1);
filteredImage = imopen(mask, se);
subplot(2, 2, 3);
imshow(filteredImage);
title('Opened Image');
%%% Measure the areas to determin minAcceptableArea show the histogram of
%%% area
% props = regionprops(filteredImage, 'Area');
% allAreas = sort([props.Area], 'descend');
% histogram(allAreas)
%%Look at the histogram.  What area do you think is the minimum size to be a valid crack?
minAcceptableArea = 20;
mask = bwareafilt(filteredImage, [minAcceptableArea, inf]);
subplot(2, 2, 4);
imshow(mask);
% 
% % Measure size of crack.
props = regionprops(mask, 'Area');
allAreas = [props.Area];
out=bwferet(mask)
% Measure the areas to know the area not to be considered
% props = regionprops(mask, 'Area');
% allAreas = sort([props.Area], 'descend')
% Get width = area / maximum length
averageWidths = sort(allAreas ./ out.MaxDiameter, 'descend');
message = sprintf('The average width = %.2f pixels.', averageWidths(1));
fprintf('%s\n', message);
caption = sprintf('Binary Image of Cracks larger than %d\nAverage width of largest = %.2f pixels', minAcceptableArea, averageWidths(1));
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
uiwait(helpdlg(message));

I got the answer of crack width as shown in attachment. My question is, as you see after filteration, there are discontinuous lines of cracks. How can I connect between them to be continuous?

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yasmin ismail 2023-3-7

编辑：Walter Roberson 2023-3-7

在 MATLAB Online 中打开

I noticed that when I reduced the minimum acceptable area the crack width decreased although the appearance of blobs in this situation, while when i increased minimum acceptable area and the blobs removed and the width increased

for example:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 10;
% Read in image and convert to gray scale.
rgbImage = imread('7004-46.jpg');
I = rgb2gray(rgbImage);
subplot(2,2,1);
imshow(I);
title('7004-46');
% Take histogram.
subplot(2,2,2);
histogram(I);
grid on;  %to make grid line
title('histogram Gray image');
% Binarize image.
threshold = 145;
xline(threshold, 'Color', 'r', 'LineWidth',2)
mask=I < threshold;
mask = imfill(mask, 'holes');
% Filter image.
se = strel('line',1, 0);
filteredImage = imclose(mask, se);
subplot(2, 2, 3);
imshow(filteredImage);
title('closed Image');
%%% Measure the areas to determin minAcceptableArea show the histogram of
%%% area
% props = regionprops(filteredImage, 'Area');
% allAreas = sort([props.Area], 'descend');
% histogram(allAreas)
%%Look at the histogram.  What area do you think is the minimum size to be a valid crack?
minAcceptableArea =20;
mask = bwareafilt(filteredImage, [minAcceptableArea, inf]);
subplot(2, 2, 4);
imshow(mask);
% 
% % Measure size of crack.
props = regionprops(mask, 'Area');
allAreas = [props.Area];
out=bwferet(mask)
% Measure the areas to know the area not to be considered
% props = regionprops(mask, 'Area');
% allAreas = sort([props.Area], 'descend')
% Get width = area / maximum length
averageWidths = sort(allAreas ./ out.MaxDiameter, 'descend');
message = sprintf('The average width = %.2f pixels.', averageWidths(1));
fprintf('%s\n', message);
caption = sprintf('Binary Image of Cracks larger than %d\nAverage width of largest = %.2f pixels', minAcceptableArea, averageWidths(1));
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
uiwait(helpdlg(message));

Image Analyst 2023-3-7

@yasmin ismail, so we don't keep bothering @Ilgin Sandalci with emails on your problem, please start your own discussion thread and I'll help you there when I get more time.

yasmin ismail 2023-3-7

I am very sorry @llgin Sandalci I didnt know that my questions are sending to him

and I have already post my questions in new discussion.

Hope @Image Analyst have time to answer them

How to measure crack width - MATLAB Answers - MATLAB Central (mathworks.com)

Sorry again

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Answer 4

Joey 2024-5-21

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/563909-concrete-crack-width-measurement#answer_1461141

The comments on using MATLAB to measure crack widths in concrete is interesting! The approach of using image processing techniques to analyze crack pixels is innovative. It seems like a potentially efficient way to quantify crack size in concrete samples.

The discussion mentions a minimum acceptable area for cracks being filtered out (minAcceptableArea = 10000). Is there a specific reason for choosing this threshold value?

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Image Analyst 2024-5-21

You can pick whatever size you want. Some cracks are just too minor to worry about fixing/patching so might as well ignore them and just concentrate on the larger ones.

Several companies and universities (Texas) have built vehicles to scan roadways as they drive along and analyze the road underneath them.

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Concrete Crack Width Measurement

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