The application of an elastic graph-matching approach to discriminate facial image regions is presented. In contrast to the dynamic link architecture introduced by the Malsburg group, our application is not an identification task but a classification task. Therefore, our approach differs in several important aspects: (1) the choice of the filter set, (2) the selection of the positions of the nodes of the graph to represent the characteristic image information, (3) the generation of a representative reference pattern needed for the calculation of the classifications, and (4) a new two-step graph-matching approach based on the simulated annealing technique. The approach was tested on facial regions taking the eye region as an example target. A classification performance for the verification of eye regions of more than 93% was achieved.
