In this study, we present a new approach to overcome the problems in face recognition associated with illumination changes by utilizing the edge images rather than intensity values. However, using edges directly has its problems. To combine the advantages of algorithms based on shading and edges while overcoming their drawbacks, we introduced “hills” which are obtained by covering edges with a membrane. Each hill image is then described as a combination of most descriptive eigenvectors, called “eigenhills”, spanning hill space. We compare the recognition performances of eigenface, eigenedge and eigenhills methods by considering illumination and orientation changes on Purdue A&R face database and showed experimentally that our approach has the best recognition performance.