In this paper, a new method to represent human ear for biometrics purposes is introduced. Even if ear has a uniform distribution of color, human external ear characteristics are considered unique to each individual and permanent during the lifetime of an adult. For these reasons ear biometrics approaches are relying on morphological ear properties. Even if ear biometrics is a young topic a variety of approaches have been proposed to characterize the ear geometry and topology. Moreover, note that the ear morphology is the biggest human head concavity, and that its convex hull complement is mainly convex. In this connection, the matching potential for ear discrimination can be effectively exploited through an Extended Gaussian Image (EGI) representation. The original EGI representation and its correspondent concrete data-structure is here applied to ear description and discussed for human authentication and identification purposes.
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