Abstract
Hyperspectral imaging systems are well established, for satellite,
remote sensing and geosciences applications. Recently, the reduction in
the cost of hyperspectral sensors and increase in the imaging speed has
attracted computer vision scientists to apply hyperspectral imaging to
ground based computer vision problems such as material classification,
agriculture, chemistry and document image analysis. Hyperspectral
imaging has also been explored for face recognition; to tackle the
issues of pose and illumination variations by exploiting the richer
spectral information of hyperspectral images. In this article, we
present a detailed review on the potential of hyperspectral imaging for
face recognition. We present hyperspectral image aquisition process and
discuss key preprocessing challenges. We also discuss hyperspectral face
recognition databases and techniques for feature extraction from the
hyperspectral images. Potential future research directions are also
highlighted