Personal identification utilizing finger surface features
In this paper we present a novel approach for personal identification, which utilizes finger surface features as a biometric identifier. Using dense range data images of the hand, we calculate the curvature-based surface representation, shape index, for the index, middle, and ring fingers. This representation is used for comparisons to determine subject similarity. Our experiments involve the use of a large data set of range images collected over time. We examine the performance of individual finger surfaces as a biometric identifier as well as the performance when using the three finger surfaces in conjunction. The results of our experiments are presented, which indicate that this approach performs well for a first-of-its-kind biometric technique.