Inclusive Skin Tone Color Space Algorithm Released
Original: Show HN: Simple algorithm and color space to generate diverse skin tones
Why This Matters
Provides developers and artists a practical, open tool for more inclusive digital representation of human diversity.
Developer Toney Alexander published an open algorithm and custom color space to procedurally generate diverse, inclusive human skin tones for use in character creators and digital art tools, mapping plausible RGB values via a spherical sampling method.
Developer Toney Alexander has released an interactive web project defining a custom color space for generating diverse human skin tones in digital contexts. The project targets applications such as character creators and digital art tools, where existing solutions — ranging from emoji's 5 preset shades to full 16,777,216 RGB options — fail to represent the realistic range of human skin diversity effectively.
The approach maps skin-plausible colors within a 3D spherical coordinate space (t, u, v), then converts them to standard RGB values using a set of linear equations. Two sampling algorithms are provided in Python: one using deterministic uniform sampling and one using rejection sampling. Both output (t, u, v) coordinates fed into a `to_rgb()` function.
Alexander describes the equations as intentionally 'good enough' — a useful starting point rather than an authoritative standard — acknowledging limitations while prioritizing accessibility and practical usability. A JavaScript-based interactive color picker is embedded on the project page, with Python and JavaScript implementations freely available in the page source for reuse. The project draws on existing digital art references, such as community 'flesh cloud' color guides, and aims to bridge the gap between overly limited and overwhelmingly open color selection systems.