A cross-device matching fingerprint database from multi-type sensors

Abstract

Databases play an important role in evaluating the performance of fingerprint identification algorithms. But which can be used to test the interoperability? That is to say, few of databases can test the performance of an algorithm on images acquired by different sensors. In order to solve the problem, we create the FingerPass cross-device matching fingerprint database which consists of almost 80 thousand fingerprint images from 90 subjects on nine different fingerprint sensors. We take both technology type and interaction type into consideration when choosing the sensors, totally different from other databases. It can test the interoperability of an algorithm at both the sensor level and the sensor type level. So we can use the FingerPass to test the performance of a cross-device matching algorithm for sensors of a specific type or different types. We apply the Ver-iFinger fingerprint recognition algorithm on it, and the experimental results indicate that the FingerPass cross-device matching database is a challenge for fingerprint algorithms.