Characterization and quantification of the skin radiance through new digital image analysis

Background/aims: The individual perception of the radiance is difficult to define and quantify because it often includes physiological and psychological attributes. Although if they are differences in the perception of the skin radiance, dermatologists and experts in cosmetology consider that the complexion must reflect the general health of an individual. The aim of this work was to determine existing conditions of skin radiance via digital image analysis, consumer's perception and experts' evaluation, and propose a mathematical model to quantify the global radiance phenomenon. Methods: A round table meeting was organized in order to have free discussions about skin radiance. The qualitative assessment of skin radiance was carried out using a self‐assessment questionnaire constructed according to the information obtained from the round table meeting. A simplified version of this questionnaire was proposed to experts. One hundred female subjects belonging to three different age groups (20–30, 30–40, 40–50 and >50 years old) participated in the study. Facial images were taken using a video imaging with visual control system to ensure consistency of images among volunteers. From these images, algorithms based on the principle of polynomial approximation, segmentation by maximalization of the entropy and the Logarithmic Image Processing model were required to extract skin radiance parameters. Multiple regression analysis was used to establish, via consumer's perception of the skin radiance and experts' evaluation studies, the degree to which each of the independent parameters contributes to the skin radiance perception. Results: All the items of the self‐assessment questionnaire explained 74% of the variation of the skin radiance. Data from experts' analysis explained 87% of the variation of skin radiance. In the two cases, skin radiance appeared to be independent of age and the presence of wrinkles. From the image analysis, we observed that the skin surface parameters explained 20% of the variation of the skin radiance expressed by experts and 24% of the variation of the skin radiance expressed by volunteers. As a result, about 80% of the variation is not explained by the instrumental data. If we combine experts' analysis and instrumental data, we obtain a mathematical model that explains 92% of the variation of the skin radiance. Conclusion: The questionnaire constructed from this brainstorming session allowed volunteers and experts to judge their perception of skin radiance more precisely. Video imaging appears as an interesting method to quantify visual properties of the skin and to visualize what the consumer perceives of skin radiance. However, the mathematical model proposed from the skin surface parameters analysis does not totally explain the global perception of skin radiance. In the future, it will be necessary to develop new data‐processing programs to quantify subjective parameters in order to validate our mathematical model.