A fully rotation invariant multi-camera finger vein recognition system

Abstract

Finger vein recognition systems utilize the venous pattern within the fingers to recognize subjects. It has been shown that the alignment of the acquired samples has a major impact on the recognition accuracy of such systems. Although a lot of work has been done in this field, there is still no approach that solves all kind of finger misplacements. In particular, longitudinal finger rotation still causes major problems. As the capturing devices evolve towards contactless acquisition, solutions to alignment problems become more important. As an alternative to rotation detection and correction, the problem can also be addressed by acquiring the vein pattern from different perspectives. This article presents a novel multi-camera finger vein recognition system that captures the vein pattern from multiple perspectives during enrolment and recognition. Contrary to existing multi-camera solutions that use the same capturing device for enrolment and recognition, the capturing devices for the proposed system differ in the configuration of the acquired perspectives. The cameras of the devices are positioned so that the recognition rates around the finger are high and that the number of cameras needed is kept to a minimum. The experimental results confirm the rotation invariance of the proposed approach.