Finding homologous points in two images of a scene is the first step in determining the parameters of a transformation model that will ultimately register the images. This chapter describes various methods for finding homologous points in two images of a scene. When a set of points in each image is given and it is required to find correspondence between the points, the problem becomes one of point pattern matching and is covered. If the type of transformation model relating the points is known, the parameters of the transformation can be determined by clustering or random sample consensus (RANSAC). The also chapter covers these topics. It further describes template matching, and discusses various similarity and distance measures used in template matching. Search strategies in template matching include coarse‐to‐fine matching, multistage matching, rotationally invariant matching, and Gaussian‐weighted matching.