Computer vision involves analyzing patterns in visual images and reconstructing the real world objects that produced them. The process in often broken up into two phases: feature detection and pattern recognition. Feature detection involves selecting important features of the image; pattern recognition involves discovering patterns in the features. We will investigate a particularly clean pattern recognition problem involving points and line segments. This kind of pattern recognition arises in many other applications, for example statistical data analysis.
Given a set of N feature points in the plane, determine every line that contains N or more of the points, and return all points involved