We investigate the effect of image processing techniques when applied as a pre-processing step to three methods of face recognition: the direct correlation method, the eigenface method and fisherface method. Effectiveness is evaluated by comparing false acceptance rates, false rejection rates and equal error rates calculated from over 250,000 verification operations on a large test set of facial images, which present typical difficulties when attempting recognition, such as strong variations in lighting conditions and changes in facial expression. We identify some key advantages and determine the best image processing technique for each face recognition method.