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Albedo Based Fake Face Detection  

Kim, Young-Shin (Sungkyunkwan University, School of Information and Communication Engineering)
Na, Jae-Keun (Sungkyunkwan University, School of Information and Communication Engineering)
Yoon, Sung-Beak (Sungkyunkwan University, School of Information and Communication Engineering)
Yi, June-Ho (Sungkyunkwan University, School of Information and Communication Engineering)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.45, no.6, 2008 , pp. 139-146 More about this Journal
Abstract
Masked fake face detection using ordinary visible images is a formidable task when the mask is accurately made with special makeup. Considering recent advances in special makeup technology, a reliable solution to detect masked fake faces is essential to the development of a complete face recognition system. This research proposes a method for masked fake face detection that exploits reflectance disparity due to object material and its surface color. First, we have shown that measuring of albedo can be simplified to radiance measurement when a practical face recognition system is deployed under the user-cooperative environment. This enables us to obtain albedo just by grey values in the image captured. Second, we have found that 850nm infrared light is effective to discriminate between facial skin and mask material using reflectance disparity. On the other hand, 650nm visible light is known to be suitable for distinguishing different facial skin colors between ethnic groups. We use a 2D vector consisting of radiance measurements under 850nm and 659nm illumination as a feature vector. Facial skin and mask material show linearly separable distributions in the feature space. By employing FIB, we have achieved 97.8% accuracy in fake face detection. Our method is applicable to faces of different skin colors, and can be easily implemented into commercial face recognition systems.
Keywords
mask; radiance; reflectance; fake face; skin color;
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