Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the

preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and

earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and

3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a

rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario

on a database of 415 subjects and 1,386 total probes.