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 comentarios
Respuestas (4)
Dio Donaika
el 16 de Jun. de 2012
5 comentarios
Walter Roberson
el 16 de Jun. de 2012
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?
Image Analyst
el 22 de Jul. de 2012
"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 comentarios
Sarhat
el 29 de Nov. de 2012
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 comentario
Image Analyst
el 29 de Nov. de 2012
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
el 12 de Ag. de 2014
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
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