In this paper we study the problem of feature point matching via a technique well known in geometry, leading to a new gradient algorithm in machine vision. The procedure does not require one to solve explicit correspondences between feature points but relies on a specific form of "spatial averaging." In this sense the estimation procedure is robust. In this paper we describe the algorithm and report simulation results.