This paper addresses the problem of face recognition using a graphical representation to identify structure that is
common to pairs of images. Matching graphs are constructed where nodes correspond to image locations and edges are
dependent on the relative orientation of the nodes. Similarity is determined from the size of maximal matching cliques in
pattern pairs. The method uses a single reference face image to obtain recognition without a training stage. The Yale
Face Database A is used to compare performance with earlier work on faces containing variations in expression,
illumination, occlusion and pose and for the first time obtains a 100% correct recognition result.