Corner detection is a technique used to detect interest points in the 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, visual search, and so on. Since we know that the corners are interesting, let's see how we can detect them.
In Computer Vision, there is a popular corner detection technique called the Harris corner detector. We construct a 2 x 2 matrix based on partial derivatives of the grayscale image, and then analyze the eigenvalues. Now what does this mean? Well, let's dissect it so that we can understand it better. Let's consider a small...
