Palmprint recognition using generalized discriminant analysis

This paper presents a novel palmprint recognition approach based on generalized discriminant analysis (GDA). The method uses GDA to extract palmprint features for palmprint recognition. GDA project palmprint images from a high-dimensional input space to a lower dimensional feature space, in which the palmprints from the different palms can be discriminated much more efficiently. The experiment results show that low equal error rate 0.36% has been obtained by the proposed method.