Analysis of correlation and construction of a predictive model of skin transparency using parameters from digital images of the face
Skin Res Technol. 2022;28:582–595
MARIN Q., HONDA T., NAKAJIMA H., OKANO Y., CHEREL M., PRESTAT-MARQUIS E. (2022)
DRC Co., Ltd., Osaka, Japon.
CIEL Co., Tokyo, Japon.
Newtone Technologies, Lyon, France.
Background: Skin transparency is a cosmetic asset highly considered by Asian women.
Resulting from complex light interactions within the skin, but still not fully understood, there is no simplemethod to measure it objectively. In this study, skin parameters from digital images were analysed to build a model predicting transparency.
Materials and methods: Initially, 71 Japanese women (between ages 50 and 60 years) were recruited. This group was then extended to 262 women (between ages 21 and 60 years). Pictures of their faces were taken with the Colorface® under diffuse light and different polarisation angles. Experts graded their transparency using pictures. Pictureswere also used to compute 958 skin colour and surface parameters from different regions of the face.
Results: In the initial group of 71 subjects, 109 parameters correlated with transparency. Half of them are from the cheek and relate to colour or colour homogeneity. If the cheek presented the largest proportion of correlated parameters, best correlations were usually found in other facial regions.Multiple regressions from some cheek parameters can predict up to 80% of transparency. Stepwise regression on parameters from 262 subjects led to a six-parameter model, which is highly correlated (R = 84.1%) with transparency. It combines skin texture, colour, colour homogeneity and gloss parameters. If half of them are from the cheek, the others are from the tear trough, the full face and the cheekbone.
Conclusion: Using parameters from digital pictures exclusively, we propose a model that accurately reflects transparency. Including parameters previously shown to relate to transparency, this model should be useful for future dermatology and cosmetic research.
KEYWORDS: Colorface®, predictive model, skin transparency, visual clues