Palmprint Anti-spoofing via Frequency Enhancement and Selection

Palmprint recognition has attracted considerable interest from researchers as a convenient and secure biometric identification technology. The majority of research on palmprint recognition focuses on enhancing recognition accuracy and speed. However, the security aspects of palmprint recognition are rarely considered. This paper proposed a palmprint anti-spoofing method, called Frequency Enhancement and Selection (FES), based on frequency-domain features. Firstly, the palmprint images are transformed using the discrete cosine transform to obtain frequency-domain features. These features are then enhanced by the frequency-domain enhancement module. Finally, the frequency channels for classification are filtered based on the gate module. In this paper, experiments are conducted on a palmprint anti-spoofing database, and the experimental results demonstrate that our method can obtain the anti-spoofing accuracy of 99.81% and can outperform other methods.