1. A computer implemented method for operating a computational device as a support vector machine to discriminate a training set of vectors corresponding to a plurality of digital images into opposing first and second classes of vectors wherein the first class of vectors corresponds to a first class of the digital images and the second class corresponds to a second class of the digital images, the method including the steps of: associating a distance parameter with each vector of the training set, the distance parameter indicating a distance from its associated vector to the opposite class; and determining a linearly independent set of support vectors from the training set such that the sum of the distances associated with the linearly independent support vectors is minimized.