ICFVR 2017: 3rd international competition on finger vein recognition

Abstract

In recent years, finger vein recognition has become an important sub-field in biometrics and been applied to realworld applications. The development of finger vein recognition algorithms heavily depends on large-scale real-world data sets. In order to motivate research on finger vein recognition, we released the largest finger vein data set up to now and hold finger vein recognition competitions based on our data set every year. In 2017, International Competition on Finger Vein Recognition (ICFVR) is held jointly with IJCB 2017. 11 teams registered and 10 of them joined the final evaluation. The winner of this year dramatically improved the EER from 2.64% to 0.483% compared to the winner of last year. In this paper, we introduce the process and results of ICFVR 2017 and give insights on development of state-of-art finger vein recognition algorithms.

State of the Art in Vascular Biometrics

“…This series of contests demonstrated the advances made in this field, e.g. the winner of 2017 improved the EER from 2.64 to 0.48% compared to the winner of 2016 [312].…”

“…these can only be analysed in the context of a visit at the corresponding institutions, including GUC45 [81], GUC-FPFV-DB [225] and GUC-Dors-FV-DB [219] (where the former are palmar and the latter is a dorsal dataset, respectively). A special case is the (large-scale) datasets of Peking University, which are only partially available, but can be interfaced by the RATE 6 (Recognition Algorithm Test Engine), which has also been used in the series of (International) Finger Vein Recognition Contests (ICFVR/FVRC/PFVR) [281,282,303,312]. This series of contests demonstrated the advances made in this field, e.g.…”