Minutiae-based Finger Vein Recognition Evaluated with Fingerprint Comparison Software

Abstract

Finger vein recognition is a biometric authentication technique based on the vein patterns of human fingers. Despite the fact that classical approaches are based on correlation, the topology of vein patterns allows the use of minutiae points for their representation. Minutiae points are the most used features for representing ridge patterns in fingerprints. In literature, it has been shown that minutiae can be used for finger vein comparison, but low image quality provokes that many spurious minutiae are extracted from them. In this work, a preprocessing method is presented, that combines classical digital image processing methods and level set theory in order to extract a set with the most reliable minutiae. The experiments were performed on two publicly available databases and different comparison methods were used for testing the representative character of the minutiae set extracted. The results showed that even though the amount of extracted minutiae is around 15-30, effective identification is possible.