Feature detection algorithms
There are a number of algorithms that can be used to detect and extract features, and we will explore most of them. The most common algorithms used in OpenCV are as follows:
Harris: This algorithm is useful to detect corners
SIFT: This algorithm is useful to detect blobs
SURF: This algorithm is useful to detect blobs
FAST: This algorithm is useful to detect corners
BRIEF: This algorithm is useful to detect blobs
ORB: This algorithm stands for Oriented FAST and Rotated BRIEF
Matching features can be performed with the following methods:
Brute-Force matching
FLANN-based matching
Spatial verification can then be performed with homography.
Defining features
What is a feature exactly? Why is a particular area of an image classifiable as a feature, while others are not? Broadly speaking, a feature is an area of interest in the image that is unique or easily recognizable. As you can imagine, corners and high-density areas are good features, while patterns that repeat themselves...
