A new method for the evaluation of makeup coverage using hyperspectral imaging

The coverage of a makeup foundation is a perceived attribute which is not captured by opacity or any other single optical property. As previous instrumental measurements do not allow us to consistently compare one product to another, we have begun exploring new parameters and analysis methods made available by hyperspectral imaging. Presumably, the coverage of makeup comes from the change in color, homogeneity, and evenness over the face after application, and the ability of the product to hide spots and other blemishes.

As a starting point to unravelling this complex topic, we define a homogeneity factor $$ which measures the change in the homogeneity of the spectra using the distribution of spectral angles in the face. We likewise define a spectral shift factor $$ which indicates the degree of spectral change after product application. To test these new parameters and the overall analysis method, we applied them to the HSI validation dataset which contains data for three makeup foundation products of different coverage levels applied to 9 models.

We find that $$ correlates with the sensory ranking of coverage. Similarly, the parameter $$ correlates with the visible color change induced by the product, and we can map the three products into distinct categories based on their effect on $$ and $$ .

Nevertheless, the homogeneity factor $$ does not fully describe coverage, and in the variability in the product effect from model to model we find evidence that we must also account for the relative color difference between the model's skin tone and the product shade among other factors.