A finger-knuckle-print authentication system based on DAISY descriptor

This paper presents an approach for finger knuckle print (FKP´s) authentication using DAISY descriptor on different knuckle combinations. Score level fusion is applied on scores of features extracted from FKPs. An improved identification rate is achieved after fusion as compared to that from the individual knuckle print. There has also been a little effort on study of feature selection. The entropy measures are employed for the feature selection. The experimental results also demonstrate the superiority of the DAISY descriptor over other features in terms of the time and accuracy.