feature-detectors from this lecture notes, and I don't quite understand the
Normalized Laplacian of Gaussian filtered image.
Here is the original image:
this is the output presented in the lecture notes, filtered by Normalized Laplacian of Gaussian with $\sigma=2.502$:
and here is mine, using
scipy.ndimage.filters.gaussian_laplace with $\sigma=2.502$:
Well, my output image is quite different from the one in the lecture notes. The background of the lecture's output is totally black, even if I did some thresholding, my output is still different from the lecture's.
Moreover, I noticed that edges almost disappeared in the lecture's output, and around each detected blob, there seems to be a ring surrounding it, like this:
Why is that? Am I using
Laplacian of Gaussian wrong?