Spectropolarimetric imaging can provide useful discriminating information for human face recognition that cannot be obtained by other imaging methods. This paper examines the ability of face recognition by using spectropolarimetric images. The Spectropolarimetric images were collected by using a CCD camera equipped with a liquid crystal tunable filter, which could capture 32 bands of images over the visible and near-infrared light (0.4μm-0.72μm). Since polarization techniques have better contrast mechanisms for tissue imaging and spectroscopy, and can also provide additional information about the structure of tissues, it is expected that better discriminate performance can be obtained by using polarimetric and spectral information than just using spectral information. An algorithm for facial characteristics analysis is presented to exploit only the spectropolarimetric information from different types of facial tissues. Experiments demonstrate that the proposed algorithm can distinguish efficiently the different facial tissues.
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