Ear Recognition based on Embryological Inspirations

Abstract

Morphological shape of the human ear presents a rich and stable information embedded on the curved 3D surface, which has invited lot attention from the forensic and engineer scientists in order to differentiate and recognize people. However, recognizing identity from morphological shape of the human ear in unconstrained environments, with insufficient and incomplete training data, dealing with strong person-specificity, and high within-range variance, can be very challenging. In continuation to our previous works, we propose to use some embryological inspirations of the human ear in order to find the autonomous components and also their locations on which we can achieve large inter-individual variations. This is especially beneficial to our research as it provides some advices on the possible changes that can be observed in the external structure of the ear. We experiment with two publicly available databases, which are IIT Delhi-1 and IIT Delhi-2, consisting of several ear benchmarks of different natures under varying conditions and imaging qualities. The experiments show excellent results beyond the state-of-theart.