A GAN-based Method for Generating Finger Vein Dataset

Abstract

Deep learning is widely used in the field of biometrics, but a large amount of labeled image data is required to obtain a well-performing complicated model. Finger vein recognition has huge advantages over common biometric methods in terms of security and privacy. However, there are very few finger vein-related datasets. In order to solve this problem, this paper proposes a GAN-based finger vein dataset generation method, which is the first attempt in the domain of finger vein dataset generation by GAN. This paper generates a total of 53,630 images of 5,363 different subjects of finger veins and validates the synthetic dataset, which provides the basis for applying complex deep neural networks in the field of finger vein recognition.