Ear Authentication using Log-Gabor Wavelets

This paper investigates a new approach for human ear identification using holistic grey-level information. We employ Log-Gabor wavelets to extract the phase information, i.e. ear-codes, from the 1D gray-level signals. Thus each ear is represented by a unique ear code or (phase template). The query ear images are compared with those in the database using Hamming distance. The minimum Hamming distance obtained from the rotation of ear template is used to authenticate the user. Our experiments on two different public ear databases achieve promising results and suggest its utility in ear-based authentication. This paper also illustrates that the phase information extracted from ear images can achieve significant performance improvement as compared to appearance-based approach employed in the literature.