Image differences detection in matlab

Question

I'm trying to find the broken ligaments for these two photos. Because the patten it got I can use the conv2 function find the general broken areas. However, it is really hard for me think how to make it tell the exact broken ligaments. Can you guys give me some idea for how to find which ligaments are broken please?

Because I'm new to this website, I can not post more photos with 2-D convolution results.

Original Picture

Broken Picture

Answer 1

Make a region growing algorithm inside each perfect square. Once you get that, calculate the area of that section.

Once you find this, calculate the remaining areas. The larger values will be the broken ligaments :)

Answer 2

This may be an interesting way to do this too. I saved the second image only as 'image.jpg'.

I = imread('image.jpg');
J = imbinarize(rgb2gray(I)); % Threshold to get a BW image.
BW = bwpropfilt(~J, 'Area', [35001, 1013283]);
imshow(BW)

shows

For selecting the area thresholds easily, I used https://www.mathworks.com/help/images/calculate-region-properties-using-image-region-analyzer.html

If you don't have a recent MATLAB version where imbinarize or bwpropfilt doesn't exist, you can use equivalent thresholding functions, and regionprops to extract all objects within the area range.

Answer 3

img = imread('unbroke.jpg');
level = graythresh(rgb2gray(img));
BW = im2bw(rgb2gray(img),level);
BW2= imdilate(imerode(BW, ones(5)), ones(5)); 
BW3 = bwmorph(BW2,'remove');
figure, imshow(BW2), hold on[![enter image description here][1]][1]

[H,T,R] = hough(BW2);
P  = houghpeaks(H,15,'threshold',ceil(0.3*max(H(:))));
x = T(P(:,2)); y = R(P(:,1));
lines = houghlines(BW2,T,R,P,'FillGap',5,'MinLength',7);

max_len = 0;
for k = 1:length(lines)
   xy = [lines(k).point1; lines(k).point2];
   plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');

   % Plot beginnings and ends of lines
   plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
   plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');

   % Determine the endpoints of the longest line segment
   len = norm(lines(k).point1 - lines(k).point2);
   if ( len > max_len)
      max_len = len;
      xy_long = xy;
   end
end

lines from unbroken image

lines from broken image

Now, you know what the line segments are do some matching. Or else find pairs of segments that would be connected (same slope + same x/y intercept) within a threshold.