Abstract: This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time, a region-based matching scheme is investigated by employing the Scale Invariant Feature Transform (SIFT) matching method. Finally, the finger-vein shape, orientation and SIFT features are combined to further enhance the performance. The experimental results on databases of 426 and 170 fingers demonstrate the consistent superiority of the proposed approach.
Qin et al. proposed a classification method that applies the SVM after combining the vein shape, orientation, and scale-invariant feature transform (SIFT) features extracted from the finger-vein image REF .
Finger-Vein Verification Based on Multi-Features Fusion
Sensors (Basel, Switzerland)
Sensors (Basel, Switzerland)
Computer Science Medicine