Genetic optimisation of illumination compensation methods in cascade for face recognition

Face detection and recognition depend strongly on illumination conditions. In this reported work, genetic algorithms are used to optimise parameters of the modified local normalisation and self-quotient image methods in cascade for illumination compensation to improve face recognition. The main novelty of the proposed method is that it applies to non-homogeneous as well as homogeneous illumination conditions. The results are compared to those of the best illumination compensation methods published in the literature, obtaining 100% recognition on faces with non-homogeneous illumination and significantly better results than other methods with homogeneous illumination.