In this paper, multivariable linear regression analysis was employed to obtain the relationship among facial geometric
features, and a discriminant function was used to evaluate the significance of different features. Finally, classification
rates were compared with different combinations of geometric features. The results showed that the geometric feature
with more significance probably improved the classification performance in the cases studied.