Multiband and spectral eigenfaces for face recognition in hyperspectral images

Zhihong Pan; Glenn E. Healey; Bruce Tromberg

doi:10.1117/12.603446

28 March 2005 Multiband and spectral eigenfaces for face recognition in hyperspectral images

Zhihong Pan, Glenn E. Healey, Bruce Tromberg

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Proceedings Volume 5779, Biometric Technology for Human Identification II; (2005) https://doi.org/10.1117/12.603446
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Spectral reflectance properties of local facial regions have been shown to be useful discriminants for face recognition. To evaluate the performance of spectral signature methods versus purely spatial methods, face recognition tests are conducted using the eigenface method for single-band images extracted from the hyperspectral images. This is the first such comparison based on the same dataset. Selected sets of bands as well as PCA transformed bands are also used for face recognition evaluation with individual band processed separately. A new spectral eigenface method which preserves both spatial and spectral features is proposed. All algorithms based on spectral and/or spatial features are evaluated under the same framework and are compared in terms of accuracy and computational efficiency.

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Zhihong Pan, Glenn E. Healey, and Bruce Tromberg "Multiband and spectral eigenfaces for face recognition in hyperspectral images", Proc. SPIE 5779, Biometric Technology for Human Identification II, (28 March 2005); https://doi.org/10.1117/12.603446

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KEYWORDS

Facial recognition systems

Hyperspectral imaging

Detection and tracking algorithms

Reflectivity

Mahalanobis distance

Spatial resolution

Imaging systems

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