Comprehensive model for characterizing skin translucency by expert grading, panel evaluation and image analysis in a Chinese population / Di Qu in INTERNATIONAL JOURNAL OF COSMETIC SCIENCE, Vol. 44, N° 5 (10/2022)  

[article]  inINTERNATIONAL JOURNAL OF COSMETIC SCIENCE > Vol. 44, N° 5 (10/2022) . - p. 500-513 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) 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 [article]

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Quantification of perception towards facial skin ideal complexion in multiple ethnic populations from clinical imaging cues / Ziqi Wu in INTERNATIONAL JOURNAL OF COSMETIC SCIENCE, Vol. 44, N° 6 (12/2022)  

[article]  inINTERNATIONAL JOURNAL OF COSMETIC SCIENCE > Vol. 44, N° 6 (12/2022) . - p. 636-649 Titre : Quantification of perception towards facial skin ideal complexion in multiple ethnic populations from clinical imaging cues Type de document : document électronique Auteurs : Ziqi Wu, Auteur ; Di Qu, Auteur ; Sarah Whitehead, Auteur ; Xiaojuan Wang, Auteur ; Jianwei Liu, Auteur Année de publication : 2022 Article en page(s) : p. 636-649 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Groupe ethnique Modèles numériques Peau -- Perception visuelle Pigmentation de la peau Statistiques Index. décimale : 668.5 Parfums et cosmétiques Résumé : - OBJECTIVE : Ideal complexion is a perceptual skin quality that is strongly influenced by cultural and ethnic background. The objectives of this study are to quantitatively characterise skin ideal complexion based on clinical image cues and to compare the perceptions of ideal - METHODS : Facial images of Indian, Chinese, Caucasian and Latino females collected using VISIA®-CR were presented to naïve panels of the same ethnicity following a two-alternative forced choice design and responses on skin ‘ideal complexion’ were obtained from 336 panellists. Panel perception was transformed logistically (d′) and projected onto a continuum (ω) following Bradley-Terry model. Image cues including skin colour and unevenness, skin shine and surface smoothness and pigmentary blotches and spots were computed using image analysis, and their relationship with ω was evaluated through multiple regression analysis. A novel skin index, namely ideal complexion score (ICS), was developed and correlated against age using linear regression. Finally, ICS was applied to evaluate treatment efficacy of a skin brightening kit on 35 female Caucasian subjects. - RESULTS : Panel perception d′ showed statistically significant (p < 0.05) correlation with the contrast of image cues for all ethnic panels (R2 = 0.74, 0.76, 0.62 and 0.46 for Indian, Chinese, Caucasian and Latino respectively) and strong correlations between perception ω and linear combinations of image cues were observed (R2 > 0.88 for all). Main effects of facial image visual cues on ideal complexion were compared: contrast of skin redness and pigmented spots and visual smoothness were important in determining ICS for all ethnicities; skin colour unevenness was more pronounced for Indian and Caucasian; skin lightness was important for Indian and Chinese; skin shine was critical for Chinese and Latino; and skin hue angle ranked higher for Caucasian. Correlations between ICS and age were observed for Indian and Caucasian (R2 = 0.55) in which ICS decreased as age increased. Twenty-nine percent improvement on ICS was observed after 12 weeks' treatment using the brightening kit compared with the baseline. - CONCLUSION : Mathematical models were successfully established to describe subjective perception towards skin ideal complexion based on objectively measured image cues for multiple ethnicities. Note de contenu : - MATERIAL AND METHODS : Photography subject recruitment - Clinical digital photography - Digital imaging analysis and image cues - Panel perception trial design - Modelling of panel perception - Statistical analysis - RESULTS AND DISCUSSION : Demographics and imaging cues - Panel perception and contrast of image pairs - Skin ideal complexion score and correlation with image cues - Aging and skin ideal complexion - Treatment efficacy and skin ideal complexion - Table 1 : Objectively measured image cues (mean and standard deviation) of four ethnic populations - Table 2 : Contrast of image cues (median and range) for pairwise image comparison of four ethnic populations - Table 3 : Standardised regression coefficients of Lasso linear regression model for four ethnic populations DOI : https://doi.org/10.1111/ics.12801 En ligne : https://drive.google.com/file/d/1ND2gkdxvtUrh2IAW_zaSDXviHbGoMQmL/view?usp=share [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=38388 [article]

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