The accurate measurement of skin color and skin spectral reflectance is becoming increasingly desirable due to its application across several domains, including medical, cosmetics, graphic arts, automation, and social science fields. While there exist robust ways to accurately measure color and spectral reflectance, these methods typically require the use of specialized instruments which are often expensive, invasive, and require expert training. Therefore, it would clearly be advantageous to develop methods that can extract accurate colorimetric and spectral data from readily-available, inexpensive digital RGB cameras. Such methodology involves overcoming several fundamental obstacles due to the limitations of RGB camera data.
The current paper reviews the importance of accurate skin color and skin spectral reflectance to several domains. The paper continues by describing an existing methodology (i.e., ColourWorker) that overcomes the limitations inherent in using RGB camera data to estimate spectral reflectance. Finally, the paper presents two experiments that test the validity of ColourWorker in estimating skin spectral reflectance. Experiment 1 compares the ground-truth skin spectral reflectance data obtained from a spectroradiometer (taken from the face of volunteers at rest) to spectral reflectance data estimated from an RGB camera using ColourWorker. Experiment 2 compares the ground-truth skin spectral reflectance data obtained from a spectroradiometer (taken from the hand of volunteers with changing physiological states) to spectral reflectance data estimated from an RGB camera using ColourWorker. The results show good performance in ColourWorker’s ability to estimate skin spectral reflectance, and suggest that performance can be improved with careful consideration of reference spectra.
Library of Congress Subject Headings
Human skin color--Measurement; Spectral reflectance; Photography--Digital techniques
Color Science (MS)
Mark D. Fairchild
Thorstenson, Christopher, "Validation of a Method to Estimate Skin Spectral Reflectance Using a Digital Camera." (2017). Thesis. Rochester Institute of Technology. Accessed from
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