Titre : |
Comprehensive model for characterizing skin translucency by expert grading, panel evaluation and image analysis in a Chinese population |
Type de document : |
document électronique |
Auteurs : |
Di Qu, Auteur ; Xiaojuan Wang, Auteur ; Jianwei Liu, Auteur ; Ziqi Wu, Auteur ; Carla Kuesten, Auteur ; Weiyi Hu, Auteur ; Hirono Totsuka, Auteur ; Yinbei Chen, Auteur |
Année de publication : |
2022 |
Article en page(s) : |
p. 500-513 |
Note générale : |
Bibliogr. |
Langues : |
Anglais (eng) |
Catégories : |
Analyse d'image L'analyse d'image est la reconnaissance des éléments contenus dans l'image. Il ne faut pas confondre analyse (décomposition en éléments) et traitement (action sur les composantes) de l'image. Chinois(e)s Modèles numériques Peau -- analyse Peau -- Anatomie Peau -- Physiologie Statistiques Translucidité (optique)
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Index. décimale : |
668.5 Parfums et cosmétiques |
Résumé : |
- Objectives : Translucent skin is an attribute widely appreciated by people in East Asian countries. There have been studies in the literature to describe the phenomenon by means of clinical grading, instrumental measurement and image analysis. However, due to its subjective and complex nature, skin translucency has not been comprehensively and rigorously characterized and modelled, particularly in the Chinese population. This study is to develop a mathematical model that quantitatively describes skin translucency from visual cues objectively measured from the skin.
- Materials and Methods : The study was designed to characterize and model skin translucency by incorporating expert evaluation, panel perception and image analysis of multiple skin visual attributes in one analysis. Faces of 36 Chinese females aged 18–65 years old were evaluated by a dermatologist to obtain clinical translucency scores. Subject pairs were formed with a relatively high and low translucency score in each pair. Their faces were judged in person by 9 panellists in paired-comparison (2-AFC) fashion to pick a ‘more translucent skin’ from each subject pair. Front-view facial images of the subjects were taken, and multiple colour and other visually perceivable skin attributes were measured using image analysis. Bradley-Terry analysis and multiple regressions were performed to correlate the panel choices of ‘more translucent skin’ with the objectively measured skin parameters.
- Results : Multiple skin colour properties affected the panel choices towards translucent skin. Among them skin tone lightness and skin glossiness had positive effects on skin translucency while the hue, colour unevenness, severity of red and dark spots affected it negatively. Subsurface light reflection and skin visual smoothness had some effect but were not statistically significant. A mathematical model was constructed to predict a person's skin translucency from objectively measured skin attributes.
- Conclusion : The subjective property of skin translucency can be characterized and quantified via a comprehensive modelling process involving clinical grading, panel evaluation, image-based measurement of skin attributes and statistical analysis. A novel skin parameter, Skin Translucency Index (STI) was established, which provides a way to measure skin translucency, making it possible to assess treatment efficacy before and after product application. |
Note de contenu : |
- MATERIALS AND METHODS : Subjects and facility - Expert grading and skin colour measurement - Panel perception - Quantification of panel perception results - Image capture and analysis - Modelling
- RESULTS AND DISCUSSION : Distributions of objectively measured skin visual attributes - Panel responses - Modelling - Validation of STI model - Application |
DOI : |
https://doi.org/10.1111/ics.12798 |
En ligne : |
https://drive.google.com/file/d/1TSp-NkxV6MaUpTS4php3e7dBzZDuuZLc/view?usp=shari [...] |
Format de la ressource électronique : |
Pdf |
Permalink : |
https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=38149 |
in INTERNATIONAL JOURNAL OF COSMETIC SCIENCE > Vol. 44, N° 5 (10/2022) . - p. 500-513