Scale-sensitive fractal analysis using the patchwork method for the assessment of skin roughness

Background/aims: As skin roughness and wrinkles are easily perceived by the consumer, quantifying skin surface structures is a vital parameter for cosmetic product development. As more tools are available for measuring three-dimensional (3-D) surface data, instead of two-dimensional (2-D) profile lines, new algorithms are desirable, to take advantage of the information gathered. Methods: The patchwork method tiles topographic data sets virtually and analyzes the change in apparent area as a function of the scale. The patchwork method and conventional 2-D profilometric analysis were applied to 24 topographic skin data sets. The data sets were derived before and after application of 15% glycerol solution on the skin of eight volunteers. Results: One hour after application, skin roughness decreased by 20.8%, as measured by conventional analysis, and by 23.3%, as measured by the patchwork method. For both methods, the differences were not significant. Conclusions: The patchwork method can be applied to skin data and renders results similar in intensity and direction to conventional 2-D analysis. It is advantageous over conventional 2-D analysis in three ways: it makes use of the full topologic information, it requires no high-pass or low-pass filtering, and it is independent of the anisotropy of the skin.