Human Biometric Identification through Brain Print

Abstract

Hidden biometrics features may induce identification of a human being without using the visual structural features. The chances of forgery are reduced substantially through hidden biometrics. We are exploring the capabilities of brain structure to be used as biometric. For this we have estimated uniqueness between the structural features of human brains corresponding to different subjects. So qualifying and quantifying the uniqueness in structure of the brain should lead to subject identification. Subject identification has been done by the brain print extracted from brain structures. The proposed approach is reliable than brain signals based biometric techniques. Our aim is to extract non-linear curves having approximate brain structural information instead of considering brain to be of predefined abstract regular shapes. The results are optimistic as we are able to extract enough number of brain curves from a securely selected slice from complete brain map ensuring the scalability of the approach.