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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.