Morphological elastic graph matching applied to frontal face authentication under optimal and real conditions
In this paper, morphological elastic graph matching is applied to frontal face authentication on databases collected either under optimal conditions or during real-world tests (i.e., access-control to buildings or tele-services via Internet in a typical office environment). It is demonstrated that the morphological elastic graph matching achieves a very low equal error rate on databases collected under optimal conditions. However its performance deteriorates in real-world experiments. The compensation for variable recording conditions, such as changes in illumination, scale differences and varying face position prior to the application of morphological elastic matching is proposed. The results obtained indicate that the proposed approach overcomes the image variations and stabilizes the performance of the authentication algorithm.