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

## TL;DR

This paper introduces a new method using hyperspectral imaging to evaluate makeup coverage by analyzing changes in skin homogeneity and color after application.

## Contribution

The paper introduces two novel parameters, αHF and βSF, derived from hyperspectral imaging to evaluate makeup coverage.

## Key findings

- αHF correlates with sensory rankings of makeup coverage.
- βSF correlates with visible color change from product application.
- Products can be categorized based on their effects on αHF and βSF.

## Abstract

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
αHF
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
βSF
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
αHF
correlates with the sensory ranking of coverage. Similarly, the parameter
βSF
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
αHF
and
βSF
.

Nevertheless, the homogeneity factor
αHF
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.