Crack Detection
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I have problem for detection for surface ceramics image, how i can detect crack surface , pls give me some advice. this my code for detect crack surface
function [img1_array, img2_array,img3_array, img4_array,Zme]= DefectScan(input_path,input_path2);
% clear all;
% close all;
I = imread(input_path2);
J = imread(input_path);
I = rgb2gray(I);
J = rgb2gray(J);
% f=figure,imshow(I);
% g=figure,imshow(J);
hy = fspecial('sobel');
hx = hy';
Iy = imfilter(double(I), hy, 'replicate');
Ix = imfilter(double(I), hx, 'replicate');
ey = fspecial('sobel');
fx = ey';
Jy = imfilter(double(J), ey, 'replicate');
Jx = imfilter(double(J), fx, 'replicate');
gradmag = sqrt(Ix.^2 + Iy.^2);
gradmag2 = sqrt(Jx.^2 + Jy.^2);
K=figure,imshow(gradmag,[]);
L=figure,imshow(gradmag2,[]);
set(K, 'visible','off');
set(L, 'visible','off');
filename = 'temp_file.jpg'
filename2 = 'temp_file2.jpg'
saveas(K, filename)
saveas(L, filename2)
i1 = imread(filename)
i2 = imread(filename2)
delete(filename)
delete(filename2)
[x, y, rgb] = ind2sub([size(i1,1) size(i1,2) size(i1,3)], find(i1 ~= 255));
A = i1(min(x):max(x)-1,min(y):max(y)-1,:);
[x, y, rgb] = ind2sub([size(i2,1) size(i2,2) size(i2,3)], find(i2 ~= 255));
B = i2(min(x):max(x)-1,min(y):max(y)-1,:);
A = rgb2gray(A)
B = rgb2gray(B)
I = edge(A,'sobel')
J = edge(B,'sobel')
3 个评论
Anton Semechko
2012-6-13
Put up a sample image so people can see what you are working with. For instructions on how you can do this, see :
http://www.mathworks.com/matlabcentral/answers/7924-where-can-i-upload-images-and-files-for-use-on-matlab-answers
Walter Roberson
2012-6-16
"We're sorry but you do not have access to this page"
Dio Donaika
2012-6-16
回答（5 个）
Dio Donaika
2012-6-16
0 个投票
5 个评论
Walter Roberson
2012-6-16
When I look at your 1.jpg I cannot see any pinholes or cracks myself ? I do see lines in the image, but those have the appearance of being just part of the texture. Are all of the lines cracks ?
Dio Donaika
2012-6-16
Image Analyst
2012-6-16
No, not really. I'd give the same answer as Walter did for 1.jpg.
Walter Roberson
2012-6-16
I see some slanted lines that are fairly straight, but those look to me like scratches rather than cracks.
I see a number of areas that are raised, but possibly the places that appear lower are instead filled with something that is optically transparent and the tile overall has a flat surface.
Could you perhaps post the images 1 and 2 again, with cracks pointed out with marks?
Dio Donaika
2012-7-22
Image Analyst
2012-7-22
0 个投票
"What do i do next to calculate crack in centimeter ?" Well, what is the size of your field of view in cm? Let's say it's 30 cm and your image width is 1000 pixels. Then your calibration factor is 30/1000 cm per linear pixel, or 30^2/1000^2 cm^2 per pixel area. So just multiply your pixel lengths or areas by those factors to get the results in cm or cm^2.
8 个评论
Dio Donaika
2012-7-22
编辑：Dio Donaika
2012-7-22
Image Analyst
2012-7-22
Use regionprops() on the binary image you showed. See my BlobsDemo for an example: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862
Dio Donaika
2012-7-22
Dio Donaika
2012-7-26
Image Analyst
2012-7-27
I think you need to add blocks to your flowchart, like "connected components labeling" (bwlabel) and "feature extraction" (or whatever you want to call the use of the regionprops() function), like I already told you above, and show you in BlobsDemo.
Dio Donaika
2012-7-28
Dio Donaika
2012-8-27
Dio Donaika
2012-8-27
Sarhat
2012-11-29
0 个投票
Hello
I have used your algorithm for Crack detection in the pavement but doesn't helped. I have made an algorithm for detection of crack based on sobel edge detection. the problem, there are lots of false positive which I want to remove and only remain the edges belong to cracks.
Regards
1 个评论
Image Analyst
2012-11-29
I don't see a question. If you have a question on MATLAB programming, you can start your own thread. But we give a lot more help on MATLAB programming and some, but not so much, on algorithm development.
vijendra sn
2014-8-12
0 个投票
Hi Dio,
I am using your code for my project work. I am not able identify the dent in the image which i have attached. Please can u help out in this regards
10 个评论
Image Analyst
2014-8-12
That code is not appropriate for dents. And, an optical image like that is not good for dents anyway. You need a profilometer image, not just a regular optical camera snapshot.
vijendra sn
2014-8-12
thanks for ur reply...
but for other images i can find dents
Image Analyst
2014-8-12
编辑：Image Analyst
2014-8-12
That's nice. Post your own new thread if you need help. Show images that work and don't work.
vijendra sn
2014-8-12
y not on this image?
Image Analyst
2014-8-12
Because they're not profilometer images and you can't get depth from optical images. Plus there's a lot of clutter in the image. And the Crystal Ball Toolbox has not been released yet.
vijendra sn
2014-8-12
But i don't need to find depth of the image just i need to find dent in the image
Image Analyst
2014-8-12
Should have posted your own question like I asked and I would have answered. I'll check again in the morning for it.
Krishna
2016-7-7
Hi Image analyst, Even I am trying to use this code to find the crack length in this image. Can you please help me with it asap, I am unable to get the proper output.
Walter Roberson
2016-7-7
Please create a new Question for that Krishna.
Preetham Manjunatha
2024-12-19
编辑：Preetham Manjunatha
2025-5-16
0 个投票
Here is the MATLAB Crack segmentation and Crack width, length and area estimation codes to calculate/estimate the crack area, width and length. In addition, this package assumes the crack is segmented either using morphological method or multiscale gradient-based or deep learning semantic segmentation methods. This package estimates the crack area, width and length (pixel scale can be provided to estimate these physical quantities). Lastly, the semantic segmentation and object detection metrics for the cracks can be found using Cracks binary class bounding box and segmentation metrics package.
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2012-6-13
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