# blob detection using Laplacian of Gaussian filter

I'm learning 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?

• I store pixel values as float64, so I think no values will be truncated. Now I kinda doubt that, my output is just edge detection, while the lecture's output is blob, right? – avocado Aug 20 '13 at 2:30