Unlike the previous features we used, local features are computed on a small region of the image. Mahotas supports computing types of features called Speeded Up Robust Features (SURF). These features are designed to be robust against rotational or illumination changes (that is, they only change their values slightly when illumination changes).
When using these features, we have to decide where to compute them. There are three possibilities that are commonly used:
- Randomly
- In a grid
- Detecting interesting areas of the image (a technique known as keypoint detection or interest point detection)
All of these are valid and will, under the right circumstances, give good results. Mahotas supports all three. Using interest point detection works best if you have a reason to expect that your interest point will correspond to areas of importance in the image...
