Personal authentication using finger knuckle surface
IEEE Transactions on Information Forensics and Security
Development of a new cryptographic construct using palmprint-based fuzzy vault
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
Human identification using Knucklecodes
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
A modular approach to gesture recognition for interaction with a domestic service robot
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
Expert Systems with Applications: An International Journal
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This paper presents a new approach to achieve the performance improvement for the traditional palmprint authentication approaches. The cohort information is used in the matching stage but only when the matching scores are inadequate to generate reliable decisions. The cohort information can also be utilized to achieve the significant performance improvement for the combination of modalities and this is demonstrated from the experimental results in this paper. The rigorous palmprint authentication results presented in this paper are the best in the literature and confirm the utility of significant information that can be extracted from the imposter scores. The statistical estimation of confidence level for the palmprint matching requires an excellent match between the theoretical distribution and the real score distribution. The performance analysis presented in this paper, from over 29.96 million imposter matching scores, suggests that Beta-Binomial function can more accurately model the distribution of real palmprint matching scores.