Increasing filter size of edge detector

14 visualizaciones (últimos 30 días)
Andrew
Andrew el 7 de Abr. de 2014
Comentada: DGM el 6 de Nov. de 2022
Hello,
I am looking at using edge detectors to detect edges in my images but I as wondering if there was a way of increasing the size of the filters? For example increase Sobel or Prewitt from a 3 x 3 array to a 5 x 5 array or bigger. I am looking to see what the effect of a larger window will have on my edge detection.
Thanks, Andrew

Respuestas (2)

Nitin
Nitin el 7 de Abr. de 2014
Editada: Nitin el 7 de Abr. de 2014
There is a nice thread on stackoverflow which might give you the values of the filter you are looking for.
  3 comentarios
Nitin
Nitin el 8 de Abr. de 2014
Sorry, I have updated my answer. Hopefully this will help
DGM
DGM el 6 de Nov. de 2022
For sake of making things local and elaborating, let's consider Daniel's Sobel-esque filters.
For a 5x5 filter, you can do
r = 2; % filter radius
[x y] = meshgrid(-r:r);
fk = x./(x.^2 + y.^2);
fk(r+1,r+1) = 0
fk = 5×5
-0.2500 -0.2000 0 0.2000 0.2500 -0.4000 -0.5000 0 0.5000 0.4000 -0.5000 -1.0000 0 1.0000 0.5000 -0.4000 -0.5000 0 0.5000 0.4000 -0.2500 -0.2000 0 0.2000 0.2500
You can simply change r to get a different size filter. If you want, you can transpose it.
If you want your output image to stay within a convenient range, you can just prenormalize the kernel depending on how you intend to apply it. If you intend to apply the filter once to get a directional derivative estimate, you can do
fk = fk/-sum(sum(fk(:,1:r))); % for single-pass
... and your image will conveniently stay within [-1 1].
If you intend to do two orthogonal filter passes to calculate the gradient magnitude, you can normalize like so:
fk = fk/(sqrt(5)*r); % for 2-pass
... and your image will stay within [0 1]
... or you can do whatever you want with it as is.

Iniciar sesión para comentar.


Image Analyst
Image Analyst el 7 de Abr. de 2014
You can try difference of Gaussians or something. Use fspecial to build the Gaussians. DOG filters are common edge filters.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by