A fingerprint spoof detection based on MLP and SVM

We introduce a fingerprint spoof detection technique based on MLP and SVM that combines several features. The proposed technique is evaluated on two scenarios: (i) when an impostor can perform consecutive attempts to be considered authentic; and, (ii) when the system deals with fingerprints from elderly people. In order to analyze these scenarios, a database was developed. The results show that the proposed combination of features increases the system performance in at least 33.56% and that the average error increases as more attempts for acceptance are allowed. The SVM classifier presents better performance in almost all the tested configurations. However, MLP is more accurate with biometrics from elderly people.