ABSTRACT
After collecting a data base of fingerprint images, we first design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images originate from the same finger. In one experiment, the neural network is trained using a few hundred pairs of images from the data base and its performance is subsequently tested using several thousand pairs. The error rate currently achieved is less than 0.5%. We then describe preliminary classification experiments. Additional results, extensions and possible applications are also briefly discussed.
