Characterising the variations in ethnic skin colours: a new calibrated data base for human skin.
BACKGROUND
Accurate skin colour measurements are important for numerous medical applications including the diagnosis and treatment of cutaneous disorders and the provision of maxillofacial soft tissue prostheses.


METHODS
In this study, we obtained accurate skin colour measurements from four different ethnic groups (Caucasian, Chinese, Kurdish, Thai) and at four different body locations (Forehead, cheek, inner arm, back of hand) with a view of establishing a new skin colour database for medical and cosmetic applications. Skin colours are measured using a spectrophotometer and converted to a device-independent standard colour appearance space (CIELAB) where skin colour is expressed as values along the three dimensions: Lightness L*, Redness a* and Yellowness b*. Skin colour differences and variation are then evaluated as a function of ethnicity and body location.


RESULTS
We report three main results: (1) When plotted in a standard colour appearance space (CIELAB), skin colour distributions for the four ethnic groups overlap significantly, although there are systematic mean differences. Between ethnicities, the most significant skin colour differences occur along the yellowness dimension, with Thai skin exhibiting the highest yellowness (b*) value and Caucasian skin the lowest value. Facial redness (a*) is invariant across the four ethnic groups. (2) Between different body locations, there are significant variations in redness (a*), with the forehead showing the highest redness value and the inner arm the lowest. (3) The colour gamut is smallest in the Chinese sample and largest in the Caucasian sample, with the Chinese gamut lying entirely the Caucasian gamut. Similarly, the largest variability in skin tones is found in the Caucasian group, and the smallest in the Chinese group.


CONCLUSIONS
Broadly speaking, skin colour variation can be explained by two main factors: individual differences in lightness and yellowness are mostly due to ethnicity, whereas differences in redness are primarily due to different body locations. Variations in lightness are more idiosyncratic probably reflecting the large influence of environmental factors such as exposure to sun.
School of Electronics and Information Engineering, University of Science and Technology Liaoning, Liaoning, China.|Department of Psychological Sciences, University of Liverpool, Liverpool, UK.
K
K
Xiao
School of Dentistry, University of Manchester, Manchester, UK.
J M
JM
Yates
School of Dentistry, University of Sulaimani, Sulaimani, Iraq.
F
F
Zardawi
Department of Imaging and Printing Technology, Chulalongkorn University, Chulalongkorn, Thailand.
S
S
Sueeprasan
National Key Lab of Colour Science and Engineering, Beijing Institute of Technology, Beijing, China.
N
N
Liao
School of Healthcare Science, Manchester Metropolitan University, Manchester, UK.
L
L
Gill
School of Electronics and Information Engineering, University of Science and Technology Liaoning, Liaoning, China.
C
C
Li
Department of Psychological Sciences, University of Liverpool, Liverpool, UK.
S
http://orcid.org/0000-0003-0080-5813
S
Wuerger
D000293:Adolescent; D000328:Adult; D000368:Aged; D002138:Calibration / Q000592:standards; D003124:Colorimetry / Q000379:methods / Q000592:standards*; D016208:Databases, Factual / Q000592:standards*; D005006:Ethnicity; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012880:Skin Pigmentation / Q000502:physiology*; D055815:Young Adult
body location; calibrated skin data base; colour space; ethnicity; skin appearance; skin colour; skin colour differences; skin colour variation; skin variation