Biometric identification using the dynamic features of the eyes

This work investigates the feasibility of using the dynamic features of the eyes for biometric identification. By leveraging the fusion of eye movement features and iris constriction and dilation parameters, we show that such dynamic features of the eye can yield a good level of accuracy for biometric systems. This was achieved by recording then classifying eye movements into segments consisting of saccades and fixations, and examining changes in the pupil size during these movements. The velocity and acceleration were computed for each segment to form a vector of features for biometric identification. We tested four types of stimuli to hypothesize which will provide a viable stimulating method for extracting eye features. The results suggest that simple stimuli such as images and graphs can excite the dynamic features of the eye for the purpose of biometric identification.