A NOVEL SIMILARITY METRIC FOR RETINAL IMAGES BASED AUTHENTICATION

In biometrics the identity of an individual is verified using some physiologic or behavioural feature. In a typical authentication process involving some biometric trait, the biometric pattern for the user is extracted (a set of feature landmarks, a characteristic vector etc...). A similarity score is calculated between these patterns to determine if they belong to the same individual or not. This work presents an analysis of similarity metrics for an authentication system in which retinal vessel feature points are used as biometric pattern. The VARIA database of retinal images is used. A new metric is defined weighting the matched points information with the previously defined metrics. The obtained results show a large stretchment of the confidence gap between the matching scores of patterns from the same individual and the matching scores of patterns from different ones.