Vision Paper: Hyperspectral Analysis of Finger Skin Reflectance for Resilient Biometric Systems

Hyperspectral imaging (HSI) outperforms the ability of RGB and multi-spectral imaging by conveying information through hundreds of contiguous wavelength intervals. This emerging technology can enable real-time monitoring of spatially resolved spectral information of materials. This paper explores the use of HSI classification to analyze the spectral structure of the human skin of fingers. The spectral reflectance of human skin is believed to vary significantly between individuals, but finding a typical signature for human skin reflectance and what its distribution is across a population are open research questions. The skin spectra acquired through a spectrograph from a diverse population are proven to be interspersed, thus the system using it would not be challenged by ethnicity. Existing related studies are using spectrophotometers only to explore features of human skin reflectance. Rather than use biochemistry, this research enables the design of image-based hand-crafted features to determine its representation. Although the lack of a biochemical component limits identity verification to extrinsic factors, reflectance has the potential as an identifying factor. As the first research to use HSI to assess reflectance, we focus on determining the extent of that potential, including its potential use in machine learning applications for identity verification.