Blob detectors with LoG, DoG, and DoH

In an image, a blob is defined as either a bright on a dark region, or a dark on a bright region. In this section, we will discuss how to implement blob features detection in an image using the following three algorithms. The input image is a colored (RGB) butterfly image.

Laplacian of Gaussian (LoG)

In the Chapter 3, Convolution and Frequency Domain Filtering, we saw that the cross correlation of an image with a filter can be viewed as pattern matching; that is, comparing a (small) template image (of what we want to find) against all local regions in the image. The key idea in blob detection comes from this fact. We have already seen how an LoG filter with zero crossing can be used for edge detection in the last chapter. LoG can also be used to find scale invariant regions by searching 3D (location + scale) extrema of the LoG with the concept of Scale Space. If the scale of the Laplacian (σ of the LoG filter) gets matched with the scale of the blob, the...