Main Article Content
Knuckle biometrics is one of the current trends in biometric human identification which offers a reliable solution for verification. This paper analysis FKP recognition based on the behaviour of two different filtering and classification methods. Firstly, Gabor Filter Banks techniques are applied for finger knuckle print recognition and then the same database is analysed against Dual Tree Complex Wavelet Transform technique. The experiment is evaluated to identify finger knuckle images using PolyU FKP database of 7920 images. Finally, these two different systems are compared for false acceptance rate FAR, true acceptance, false rejection rate FRR and true rejection. Extensive experiments are performed to evaluate both the techniques, and experimental results show the pros and cons of using both the techniques for specific applications.
How to Cite
, H. P. E. H. S. (2015). Finger Knuckle Analysis: Gabor Vs DTCWT. International Journal on Recent and Innovation Trends in Computing and Communication, 3(5), 3371–3376. https://doi.org/10.17762/ijritcc.v3i5.4454