Multi-stage face recognition for biometric access

Protecting the privacy of user-identification data is fundamental to protect the information systems from attacks and vulnerabilities. Providing access to such data only to the limited and legitimate users is the key motivation for `Biometrics´. In `Biometric Systems´ confirming a user´s claim of his/her identity reliably, is more important than focusing on `what he/she really possesses´ or `what he/she remembers´. In this paper the use of face image for biometric access is proposed using two multistage face recognition algorithms that employ biometric facial features to validate the user´s claim. The proposed algorithms use standard algorithms and classifiers such as EigenFaces, PCA and LDA in stages. Performance evaluation of both proposed algorithms is carried out using two standard datasets, the Extended Yale database and AT&T database. Results using the proposed multi-stage algorithms are better than those using other standard algorithms. Current limitations and possible applications of the proposed algorithms are also discussed along, with further scope of making these robust to pose, illumination and noise variations.