A modular architecture based on image quality for fingerprint spoof detection

This work proposes an improvement for fingerprint spoof detection in order to reduce the occurrence of live fingerprints from elderly people taken as spoof. The novel architecture combines classifiers working independently into two distinct image quality groups. The results show that high quality spoof images are easily detected, the misclassification rate for live fingerprints is reduced by 64.0% and the overall system performance increases 49.61%.