Finger surface as a biometric identifier
Computer Vision and Image Understanding
Finger surface as a biometric identifier
Computer Vision and Image Understanding
On the Relevance of Image Acquisition Resolution for Hand Geometry Identification Based on MLP
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Feature level fusion of multi-instance finger knuckle print for person identification
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Identity verification utilizing finger surface features
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
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Biometrics, the discipline of establishing an individual's identity based upon physical or behavioral characteristics, has become of major research area due to the numerous applications for reliable personal identification. The performance of a biometric system is highly dependent on the chosen biometric identifier. We present a novel approach for personal identification which utilizes 3D finger surface features as a biometric identifier. Using 3D range images of the hand, a surface representation for the index, middle, and ring finger is calculated and used for comparison to determine subject similarity. We use the curvature based shape index to represent the fingers' surface. A large unique database of hand images supports the research. We use data sets obtained over time to examine the performance of each individual finger surface as a biometric identifier as well as the recognition performance obtained when combining them. The probe and gallery sets sizes are varied to determine their affect on overall system performance. We present performance results for both authentication and identification tasks which suggest, that, 3D finger surface is a viable choice as a biometric identifier.