Bernhard Prommegger, Georg Wimmer and Andreas UhlBrömme, ArslanDamer, NaserGomez-Barrero, MartaRaja, KiranRathgeb, ChristianSequeira Ana F.Todisco, MassimilianoUhl, Andreas2022-10-272022-10-272022978-3-88579-723-4https://dl.gi.de/handle/20.500.12116/39703If biometric systems are rolled out on a large scale, it will not always be guaranteed that all capturing devices are of exactly the same type. It is therefore important to ensure that the biometric system also works across multiple capturing devices. In finger vein biometry, there is almost no published work in this regard. The biggest problem here is certainly that there are only very few datasets (recorded by different institutions) that usually have no overlap at all with the test persons contained. In a first approach, this article tries to examine how well cross-sensor finger vein recognition works. For the investigation, four publicly available datasets, which were acquired with four different devices in three different scenarios, were evaluated. Using three different finger vein recognition approaches, we will show that the results distinctly deteriorate in cross-sensor recognition scenarios compared to the recognition results using only images from the same device, even more so for image data from contact-less and contact-based capturing devicesenFinger Vein RecognitionCross-Sensor RecognitionText/Conference Paper10.1109/BIOSIG55365.2022.98969621617-5493