LFMB-3DFB: A Large-scale Finger Multi-Biometric Database and Benchmark for 3D Finger Biometrics

Finger contains several discriminative biometric traits, including fingerprint, finger vein, finger knuckle, and finger shape, which are complementary in identity information. However, in most current researches and practical applications, only a single or several traits are utilized, which are prone to unsatisfactory recognition performance and easy forgery. Our work is the first attempt to collect and study all biometric traits on the finger. Firstly, a novel multi-view, multi-spectral 3D finger imaging system is designed. To the best of our knowledge, it is the first biometric imaging system that can capture almost all finger-based traits. With this 3D finger imaging system, we scanned numerous fingers, acquiring their external skin images and internal vein images from 6 different views. Then 3D finger models with skin and vein textures are reconstructed by space carving, mesh regularization, and texture mapping algorithms. Secondly, we establish a benchmark dataset, namely the Large- scale Finger Multi-Biometric database and benchmark for 3D Finger Biometrics (LFMB-3DFB). LFMB-3DFB contains 695 fingers, and each finger is captured 10 times. Then, 6 finger skin images and 6 finger vein images are obtained for each acquisition, and final 83,400 images and 6,950 3D finger models are obtained. Besides, we designed a more rigorous and comprehensive evaluation protocol for both identification and verification tasks. Finally, we designed corresponding baselines for 2D finger traits recognition, multi-view finger traits recognition, 3D finger traits recognition, and score-level fusion. Rigorous experiments have been conducted to verify the significance and usefulness of the proposed LFMB-3DFB.