Environmental Illumination Invariant Face Recognition using Near Infrared Imaging System

Environmental illumination can degrade performance of face recognition systems. This paper presents a method to reduce the effect of environmental illumination for face recognition with near infrared (NIR) imaging systems. The camera response function that maps the image irradiance to image brightness is estimated via principal component analysis with pairs of facial images taken under different lighting conditions. The inverse of camera response function is used to map two facial images of a subject taken with and without frontal NIR lighting under ambient light. The irradiance of facial image with frontal NIR lighting in the absence of ambient light is estimated using the inverse camera response function. Then the brightness image with only the frontal NIR lighting is obtained from the irradiance to be used for face recognition. Since the brightness images are used by face recognition system when there is no ambient light, the same face recognition algorithm and database can be used without any modification. The proposed method is a pre-processing method and does not require additional hardware. Performance is evaluated and compared to existing methods at various false matching rates. The proposed method can enhance the performance of face recognition in the presence of ambient light at false matching rates at which practical biometric authentication systems operate