Multiview-multiband face recognition system to solve illumination and pose variation

Identifying faces under the influence of illumination and pose can be challenging as the presence of two variations on the same image can greatly change the appearance of a person. Thus, in this paper, we propose a multiview face recognition system that is able to solve illumination and pose face recognition problems. The proposed system uses multiband feature technique to extract features that are invariant to illumination variation and parallel radial basis function neural networks to train different poses. The recognition performance of the proposed system is validated against the Yale B database and compared to other systems implemented on the same database.