1. A digital image processing method for locating eyes on a frontal face digital image, comprising the steps of: a) obtaining a digital image of a frontal face, W pixels wide and H pixels high, grayscale, where the top left vertex of the digital image is considered as the reference source; b) detecting each eye, starting with a search subimage of the frontal face digital image, delivering approximate coordinates if both eyes have been detected, or an arbitrary predetermined value that indicates no eye detection; c) locating the iris of each eye, if both eyes have been detected, starting from the approximate coordinates, validating the frontal face on the digital image providing eye positions; or d) validating the frontal face digital image, if one or both eyes have not been detected, calculating a search subimage defined by an area resulting from centering a square of area L on the original image, where L=0.8×W, to deliver the coordinates for the eyes; wherein the step of validating the frontal face digital image is comprised of the steps of: 1) defining a search subimage by an area resulting from centering a square of area L on the original image; 2) submitting the search subimage to an Adaboost cascade classifier that uses Haar features, which has previously been trained with images that include both eyes and nose; if the output is negative the frontal face input image is rejected; if the output is positive the following steps are executed: (i) estimating the left eye coordinates (X i ,Y i ) such that X i is in position 0.21×L pixels and Y i =0.54×L pixels with respect to the input frontal face image; (ii) estimating the right eye coordinates (X d ,Y d ) such that X d is in position 0.83×L pixels and Y d =0.54×L pixels with respect to the input frontal face image; and (iii) delivering the coordinates obtained for each eye (X i ,Y i ) and (X d ,Y d ).