A correlation-based approach to automatic face recognition requires adequate normalization techniques. If the positioning of the face in the image is accurate, the need for shifting to obtain the best matching between the unknown subject and a template is drastically reduced, with considerable advantages in computing costs. In this paper, a novel technique is presented based on a very efficient eyes localization algorithm. The technique has been implemented as part of the “electronic librarian” of MAIA, the experimental platform of the integrated Al project under development at IRST. Preliminary experimental results on a set of 220 facial images of 55 people disclose excellent recognition rates and processing speed.