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An image‐based mapping of significance and relevance of facial skin colour changes of females living in Thailand
Author(s) -
Séroul P.,
Campiche R.,
Gougeon S.,
Cherel M.,
Rawlings A.V.,
Voegeli R.
Publication year - 2020
Publication title -
international journal of cosmetic science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.532
H-Index - 62
eISSN - 1468-2494
pISSN - 0142-5463
DOI - 10.1111/ics.12593
Subject(s) - forehead , cheek , clinical significance , artificial intelligence , computer vision , computer science , medicine , anatomy , pathology
Objective There are methods to evaluate skin colour on defined areas over the face but no approach automatically and accurately evaluates skin colour variations on large facial areas, comparing subjects, treatments and/or time points. We propose such an image‐based approach to visualize quickly the outcome of clinical studies on colour variations. Methods Among 54 Asian women, one group applied a vehicle twice daily, during 28 days, and the other group an anti‐ageing emulsion, taking facial images at baseline and after treatment. Changes in L * a * b * values were studied on four pre‐selected facial regions. We also reconstructed average facial images from which the L * a * b * parameters were extracted for every pixel, computing relevance (Δ E ) and significance data. Using colour gradients, we mapped these results onto the average facial images. Results After treatment, L * a * b * parameters show no statistically relevant colour changes in the vehicle group. In the ‘active’ group, skin was lighter at the upper cheek and, overall, redness decreased. Relevance and significance maps confirmed no visible colour changes in the vehicle group. In the ‘active’ group, the mapping approach revealed colour changes and their location. Skin became lighter below the eye, cheek and forehead. It was less red below the eyes, on the cheek, jawline and forehead, and generally more yellow. Conclusion Our image‐based mapping approach proves to be powerful. It enables us to identify precise facial regions of relevant and statistically significant colour changes after a topical treatment, regions that would have otherwise been undetected.