Uniformness Algorithm

About Algorithm

Disclaimer about natural skin behaviour that might affect results stability:

Skin uniformness is not a scientifically correct term, as multiple factors and different pigments can alter the visual appearance of the skin. Also, visual skin uniformness may significantly differ from natural skin uniformness, if cosmetics such as foundations, concealers, BB creams, CC creams, colour correctors, or setting powders are applied to the skin before taking the photo.

Disclaimer about algorithm sensitivity:

The Uniformness Algorithm is sensitive to a spatial resolution of the image.

Insufficient image spatial resolution (less than 2500 pixels) may lead to insufficient detection of skin texture local non-uniformness.

1. This Algorithm estimates the visible skin texture non-uniformness, such as eruptions, age spots, freckles, and blood vessels close to the surface, along with texture-associated skin features.

2. This Algorithm estimates indicated skin health parameters on: forehead, right cheek, left cheek areas.

3. The Main Metric for this Algorithm is the Uniformness Score, with a range from 0 to 100.

   1. Values from 80 to 100 are considered a relatively good skin condition with relatively uniform texture skin.

   2. Values from 50 to 70 are considered as skin with visible skin texture non-uniformness.

   3. Values below 50 are considered as an alerting skin condition, that might require specialist attention.

   4. Uniformness Score is a non-linear transformation of a spatial information about non-uniform skin texture clusters.

4. There are no Submetrics for this Algorithm.

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Algorithm API

API access is available only for Professional plan clients

See Uniformness Result Scheme.

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