Face verification and rejection with illumination variations using MINACE filters

A face verification system based on the use of a minimum noise and average correlation energy (MINACE) filter for each person is presented that functions with illumination variations present. A separate filter is used for each person; it is a combination of different training images of only that person. The system is tested using both unregistered and registered images from the CMU Pose, Illumination and Expression (PIE) database. The number of correct (PC) and the number of false alarm (PFA) scores are compared for the two cases. Rather than using the same parameters for the filter of each person, an automated iterative filter training and synthesis method is used. A validation set of several other faces is used to achieve parameter selection for good rejection performance. For filter-evaluation, all filters are tested against all images, but the same peak threshold is used for each filter to determine verification and rejection.

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