This paper is focused on algorithmic issues for biometric face verification (i.e., given an image of the face and an identity claim, decide whether they correspond to each other or not). Several alternatives for geometric normalization of images, photometric normalization, dimensionality reduction and similarity measures are proposed and compared using the XM2VTS database and the associated Lausanne protocol [10], [11]. Experiments under this particular framework show that best verification results are obtained when holistic approaches for face recognition (such as eigenfaces or fisherfaces) are combined with techniques traditionally associated to local feature-based approaches, such as Gabor decompositions.