Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Person Identification Using Multiple Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Fingerprint and Speaker Verification Decisions Fusion
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Communications of the ACM - Multimodal interfaces that flex, adapt, and persist
An Improved Score Level Fusion in Multimodal Biometric Systems
PDCAT '09 Proceedings of the 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies
Performance evaluation of score level fusion in multimodal biometric systems
Pattern Recognition
Personal verification using palmprint and hand geometry biometric
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Fusion of face and iris features for multimodal biometrics
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A review of speech-based bimodal recognition
IEEE Transactions on Multimedia
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
A finger vein image quality assessment method using object and human visual system index
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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To overcome the influence of image quality on single-mode recognition systems, a novel fingerprint and finger vein dual-mode recognition algorithm based on image quality evaluation is proposed. This method fuses the image quality scores of both fingerprint and finger vein in a novel way, to overcome the influence of image quality on identification results. Two classifiers are then designed for fingerprint and finger vein recognition, respectively. The final recognition is achieved by the fusion of the two quality scores and classifiers' recognition results at the decision level. This is a novel quality evaluation of both fingerprint and finger vein. This method not only overcomes the limitations of image quality on single-modal biometrics, but also effectively improves the recognition performance of the system, thus demonstrating the validity of the method when used for multimodal biometric identification.