Im using sobel edge detection.
How does Matlab, by itself manage to achieve very thin edges like this one (using just the Matlab's edge function with 'sobel' as parameter)
matlabsobel = edge(originalImage,'sobel')
imshow(matlabsobel)
but when I try to do sobel algorithm my own way, assuming the process is just the same..
originalImage = gaussianizedimage;
threshold = 60.5;
k = [1 2 1; 0 0 0; -1 -2 -1];
H = conv2(double(originalImage),k, 'same');
V = conv2(double(originalImage),k','same');
E = sqrt(H.*H + V.*V);
edgeImage = uint8((E > threshold) * 255);
imshow(edgeImage);
title('sobel algorithm')
Why is that its different? What is still lacking in my implementation to achieve Matlab's thin edges? Can anyone provide code to make it look/similar to Matlab native sobel edge detection?
Thanks

 Akzeptierte Antwort

Image Analyst
Image Analyst am 21 Aug. 2014

1 Stimme

edge() takes a grayscale edge image like you'd get with imgradient(), and then thresholds it and skeletonizes the thresholded image, like you'd get with bwmorph(BW, 'Skel', inf).

4 Kommentare

Ivan Matala
Ivan Matala am 21 Aug. 2014
@Image Analyst
thanks for you answer,,, Ive searched bwmorph and if by chance,, do you what is the best suited morphological operation to make it look like the 1st image above?
Thanks
I told you that already. Here is is again, formatted as code this time:
thinEdgeImage = bwmorph(thresholdedImage, 'Skel', inf);
Miroslav Hagara
Miroslav Hagara am 19 Sep. 2018
Bearbeitet: Miroslav Hagara am 19 Sep. 2018
according this, if I use this code:
BW1 = edge(I,'Prewitt');
BW2NT = edge(I,'Prewitt','nothinning');
BW2 = bwmorph(BW2NT, 'Skel',Inf);
I should get the same pictures. But this is not true.
I have get better result with
BW2 = bwmorph(BW2NT, 'thin', Inf)
but still without same pictures.
If you look inside edge() you will see:
if thinning
e = computeedge(b,bx,by,kx,ky,int8(offset),100*eps,cutoff);
else
Which does the magic.
MathWorks doesn't specify what's done there.

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