Corner detection is a technique used to detect points of interest in an image. These interest points are also called feature points, or simply features, in computer vision terminology. A corner is basically an intersection of two edges. An interest point is basically something that can be uniquely detected in an image. A corner is a particular case of an interest point. These interest points help us characterize an image. These points are used extensively in applications such as object tracking, image classification, and visual search. Since we know that the corners are interesting, let's see how can detect them.
In computer vision, there is a popular corner detection technique called the Harris corner detector. We basically construct a 2 x 2 matrix based on partial derivatives of the grayscale image, and then analyze the eigenvalues. What does that even mean? Well, let's dissect it so that we can understand it better. Let's consider a small...