The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Signal Processing Handbook
Digital Signal Processing Handbook
Implementing Biometric Security
Implementing Biometric Security
Robust Real-Time Face Detection
International Journal of Computer Vision
Biometrics and Network Security
Biometrics and Network Security
Using Continuous Face Verification to Improve Desktop Security
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Continuous Verification Using Multimodal Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Impostor Users Discovery Using a Multimodal Biometric Continuous Authentication Fuzzy System
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Video-based face recognition using adaptive hidden markov models
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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With the increasing use of computers nowadays, information security is becoming an important issue for private companies and government organizations. Various security technologies have been developed, such as authentication, authorization, and auditing. However, once a user logs on, it is assumed that the system would be controlled by the same person. To address this flaw, we developed a demonstration system that uses facial recognition technology to periodically verify the identity of the user. If the authenticated user's face disappears, the system automatically performs a log-off or screen-lock operation. This paper presents our further efforts in developing image preprocessing algorithms and dealing with angled facial images. The objective is to improve the accuracy of facial recognition under uncontrolled conditions. To compare the results with others, the frontal pose subset of the Face Recognition Technology (FERET) database was used for the test. The experiments showed that the proposed algorithms provided promising results.