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.
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Mitra, S., Savvides, M., Kumar, B.V.K.V. (2005). Facial Asymmetry: A New Robust Biometric in the Frequency Domain. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_129
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DOI: https://doi.org/10.1007/11559573_129
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
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