Fingerprint processing using back propagation neural networks

A system for the extraction of minutiae from gray-scale fingerprint images using back-propagation networks and Gabor filters is described. Good detection ratios and low false alarm rates were achieved. The importance of having good input representations of the image data is illustrated through variations in the performance of different trained networks. The usefulness of Gabor filters in the representation processing layer is demonstrated