CODEWITHSUNDEEP
matlabimage-processingedge-detection
Daniel R.
Daniel R.

Reputation: 784

How to find edge from dark line to grey smeared region

I am trying to detect the edge from black horizontal line to the gray-smeared foreground. The desired edge/result is slightly marked red.

Desired Result

What have I tried so far :

My approach was to use the standard Chan-Vese Segmentation combined with several preprocseeing methods like gaussian blurring, maximum filter or morpholigocal operator like erosion. However, when I am initializing the level set function at the lower part of the image, the contour gets stuck right before the dersired edge.

Chan-Vese result

Due to the noise I can't get rid off without destroying important information of the image, simple methods like the sobel or prewitt filtering might fail.

Another apporoach of me was to search for the maximum/minimum intensity columnwise of the image and mark the darkest pixel per column. As you can assume, this will fail too because the edge I am looking for is not the only part that has dark pixels, that's why this method is very error-prone.

Edit

Snakes does not help either.

Active Contour with Snakes

The active contour, marked as blue, simply goes over the edge and at the left and right the contour gets stuck. The Code I tried wasthe function Snake2D(I,P,Options) taken from here.

Here is the original image if you would like to help me.

Original Image

Upvotes: 2

Views: 327

Answers (1)

lhcgeneva
lhcgeneva

Reputation: 1981

I think your approach using the rows and finding the maximum is probably easiest. The one problem you have is distinguishing the two main maxima. For this, you can apply a rough smoothing, to find the middle between the two maxima (blue line in image below). You can then only take the lower bit, which is the one you are interested in and find the maximum of this bit. In a final step, just add up the two indices.

Result: enter image description here

Could go like this:

ib = imread('LHkm2.png');   %Read image
sz = size(ib);              %get dimensions
for i = 1:sz(2)
    [~, ind_mid(i)] = max(smooth(-double(ib(:, i)), 130));%First round
    line_to_smooth = ib(ind_mid(i):end, i);%Get line with one maximum
    [~, ind(i)] = min(smooth(double(line_to_smooth), 10));%Second round
    ind(i) = ind(i) + ind_mid(i);%Add indices to get final position
end
imshow(ib,[]);
hold on;
plot(ind_mid, 'LineWidth', 3);
plot(ind, 'LineWidth', 3);

Note: You can of course smooth the final line just like any other graphs to get rid of bumps like this:

ind = smooth(ind, 10)

where 10 is your smoothing window (the higher the broader, see here.

Upvotes: 2

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