Support vector machine for hand geometry-based identity verification system
Łukasz A. Stasiak · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
A new approach to classifying the hand geometry features for personal verification is presented. This paper attempts to improve the performance of hand geometry-based systems by applying the Support Vector Machine (SVM) to the template classification task. We also compare the SVM-based approach to vector distance-based and neural network-based approaches as well as to other systems described in the literature and to the popular commercial systems. The testing results show that our system is competitive to the other known solutions.