%0 Journal Article
%T State of the Art: Signature Biometrics Verification
%A Mohamed Soltane
%A Noureddine Doghmane
%A Nourddine Guersi
%J Brain. Broad Research in Artificial Intelligence and Neuroscience
%D 2010
%I EduSoft publishing
%X This paper presents a comparative analysis of the performance of three estimation algorithms: Expectation Maximization (EM), Greedy EM Algorithm (GEM) and Figueiredo-Jain Algorithm (FJ) - based on the Gaussian mixture models (GMMs) for signature biometrics verification. The simulation results have shown significant performance achievements. The test performance of EER=5.49 % for "EM", EER=5.04 % for "GEM" and EER=5.00 % for "FJ", shows that the behavioral information scheme of signature biometrics is robust and has a discriminating power, which can be explored for identity authentication.
%K Biometric authentication
%K behavioral
%K signature
%K soft decision and Gaussian Mixture Modal
%K EM
%K GEM and FJ
%U http://brain.edusoft.ro/index.php/brain/article/view/43