Comparison of Spectral-Only and Spectral/Spatial Face Recognition for Personal Identity Verification. (26th May 2009)

• Record Type: Journal Article
• Authors: Pan, Zhihong; Healey, Glenn; Tromberg, Bruce
• Other Names: Bowyer Kevin Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2009(2009)
• Publication Date: 2009-05-26
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2009/943602
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Face recognition based on spatial features has been widely used for personal identity verification for security-related applications. Recently, near-infrared spectral reflectance properties of local facial regions have been shown to be sufficient discriminants for accurate face recognition. In this paper, we compare the performance of the spectral method with face recognition using the eigenface method on single-band images extracted from the same hyperspectral image set. We also consider methods that use multiple original and PCA-transformed bands. Lastly, an innovative spectral eigenface method which uses both spatial and spectral features is proposed to improve the quality of the spectral features and to reduce the expense of the computation. The algorithms are compared using a consistent framework.