A novel approach based brain biometrics: Some preliminary results for individual identification

Abstract

Numerous anatomical studies of the human brain have shown a significant inter-individual variability of brain characteristics. Specifically, the extracted characteristics are used in our application as a biometric tool to identify individuals. For this purpose, Magnetic Resonance Imaging (MRI) images are considered. We show that using a single slice from an MRI volumetric image, acquired at a given level, one can extract significant brain codes that can be used for the purpose to identify individuals. Explicitly, the proposed biometric approach uses some coding techniques that are commonly employed for iris identification. Specifically, 1D log Gabor Wavelet has been considered for feature extraction. Finally, the proposed algorithm is evaluated on the Open Access Series of Imaging Studies (OASIS) database containing brain MRI Images. Results using 210 classes show that high accuracy of 98.25% to identify individuals are obtained.