Abstract
Biometrics-based authentication is an effective approach which is used for automatically recognizing a person's identity. Recently, it has been found that the finger-knuckle-print (FKP), which refers to the texture pattern produced by the finger knuckle bending, is highly unique and can be used as a biometric identifier. In this paper, we present an effective FKP recognition scheme for personal identification and identity verification. This method is a new encoding scheme based on local binary pattern (LBP). Each image first is decomposed in several blocks, each block is convolved with a bank of Gabor filters and then, the LBPs histograms are extracted from the convolved images. Finally, a BioHashing approach is applied on the obtained fixed-length feature vectors. Extensive experiments conducted over the Poly-U FKP database demonstrated the efficiency and effectiveness of our proposed method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
