A fingerprint spoof detection based on MLP and SVM

Abstract

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.

A comprehensive survey of fingerprint presentation attack detection

“…Marasco and Sansone [62] utilized a feature set combined of the residual noise of the fingerprint image to detect the coarseness of the artificial fingerprint, first-order statistics based on the gray level of each pixel, the intensity distribution to detect PAIs and the individual pore spacing, which is unique to every human. An SVM, decision tree, MLP and Bayesian classifier were chosen as classifiers, depending on the best performance per sensor.…”

Presentation attack detection methods for fingerprint recognition systems: a survey

“…Pereira et al . [43] have combined a number of features that have been suggested by the previous research. They use individual pore spacing, residual noise, multiple features based on the first‐order image statistics, features based on the ratios between the darker and the brighter pixels and features based on the strength and the clarity of the ridge structure.…”

Spatial surface coarseness analysis: technique for fingerprint spoof detection

“…According to Roberts [2], one way to overtake the security of those systems is providing to the sensor a fake physical biometric. Thus, an efficient technique for spoof detection [3,4] is an essential requirement for any fingerprint based system in operation.…”