Facial asymmetry: a new robust biometric in the frequency domain

Authors:
Sinjini Mitra;Marios Savvides;B. V. K. Vijaya Kumar
Affiliations:
Department of Statistics, Carnegie Mellon University, Pittsburgh, PA;Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA;Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

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Abstract

The present paper introduces a novel set of facial biometrics defined in the frequency domain representing “facial asymmetry”. A comparison with previously introduced spatial asymmetry measures suggests that the frequency domain representation provides an efficient approach for performing human identification in the presence of severe expressions and also for expression classification. Feature analysis indicates that asymmetry of the different regions of the face (e.g., eyes, mouth, nose) help in these two apparently conflicting classification problems. Another advantage of our frequency domain measures is that they are tolerant to some form of illumination variations. Error rates of less than 5% are observed for human identification in all cases. We then propose another asymmetry biometric based only on the Fourier domain phase and show a potential connection of asymmetry with phase.