A New Multispectral Method for Face Liveness Detection

• Published in: Proceedings - IEEE Computer Society Conference on Pattern Recognition and Image Processing pp. 922 - 926
• Main Authors: Yueyang Wang, Xiaoli Hao, Yali Hou, Changqing Guo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2013
• Subjects: Cameras; Face; Face liveness detection; Feature extraction; Hair; Lighting; multispectral imaging; reflectance; Reflectivity; Skin
• ISSN: 0730-6512
• DOI: 10.1109/ACPR.2013.169

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.