The Harris corner detector
My last computer vision assignment had a very cool component, so I thought I’d share it. We were supposed to implement Harris’ corner detector, which is a method for detecting corners in an image. By a “corner” we usually mean the point at which a pair of edges cross each other. For the purposes of this method though, a corner is a pixel such that the intensities (of one of the RGB channels) within a small neighbourhood around it are significantly different than the intensities in the neighbourhood of a nearby pixel. A more detailed explanation of why the method works and how to implement it can be found here. These are the results of the algorithm, applied first to a simple image consisting of rectangles and then a real image (keep in mind that a threshold had to put on the number of corners marked on the image to avoid cluttering it):
