Linear discriminant feature selection techniques in elastic graph matching

In this paper, we investigate the use of discriminant feature selection techniques in the elastic graph matching (EGM) algorithm. State of the art and novel discriminant dimensionality reduction techniques are used in the node feature vectors in order to extract discriminant features. We illustrate the improvements in performance in frontal face verification using a modified multiscale morphological analysis for forming the node feature vectors. All experiments were conducted in the XM2VTS database.