A New Multispectral Method for Face Liveness Detection

Abstract

A face recognition system can be deceived by photos, mimic masks, mannequins and etc. And with the advances in the 3D printing technology, a more robust face liveness detection method is needed. In this paper, a gradient-based multispectral method has been proposed for face liveness detection. Based on two spectral bands, the developed method is tested for the classification of genuine faces and common disguised faces. A true positive rate of 96.7% and a true negative rate of 97% have been achieved. The performance of the method is also tested when face rotation occurs. The contributions of this paper are: First, a gradient-based multispectral method has been proposed. Except for the reflectance of the skin regions, the reflectance of other distinctive regions in a face are also considered in the developed method. Second, the method is tested based on a dataset with both planar photos and 3D mannequins and masks. The performance on different face orientations is also discussed.