Color Theory: How to convert Munsell HVC to RGB/HSB/HSL

Question

I\'m looking at at document that describes the standard colors used in dentistry to describe the color of a tooth. They quote hue, value, chroma v

Answer 1

There is a free R package munsell which will (among other things) convert Munsell codes to RGB:

R> library(munsell)
R> mnsl2hex("5PB 5/10")
[1] "#3B75BB"

Answer 2

Despite this old post, to update Steve's answer, here are "corrected" links to RIT's repositories of Munsell data:

https://www.rit.edu/cos/colorscience/rc_munsell_renotation.php

And a direct link to spreadsheet of the sRGB converted values of the "real" Munsell colors:

http://www.rit-mcsl.org/MunsellRenotation/real_sRGB.xls

It's a spreadsheet which includes a conversion from Munsell HVC notation to xyY, then to XYZ_C, then converted to D65 illuminant, then to floating point sRGB, then quantized to 8bit sRGB values (which they call dRGB).

As for the OP's question: sRGB is (obviously) an RGB additive color model. But the differences to other color models such as subtractive CMYK are complex enough that a "simple" algorithm won't handle the conversion — while color model transformations can be approximated with a matrix, more often a LUT (Look Up Table) is preferred, such as a LUT in an ICC profile or a 3D LUT as used in film production. (Not all ICC profiles are LUT based, but a LUT based conversion IMO is what is needed here).

The Munsell data certainly falls into this category, as not only is it a different color model, it is not only a subtractive model it is based on perception, while sRGB is based on a simple relationship between red green and blue light.

The spreadsheet is the useable look-up-table, so then a program to convert things like your dental chart to sRGB would take in that data and reference the LUT contained in the spreadsheet, and return the sRGB values.

Side Note: I want to mention for clarity that although some color-space or color-model transforms can be done reasonably with an algorithm/matrix, 3D LUTs are preferred particularly when the LUTs are created from measured data of a given color-model/space, which maps the many non-linearities inherent in some models.

An extreme example is an sRGB image on your computer monitor vs how that image is printed onto paper and appears on the cover of a magazine sitting on a newsstand illuminated with florescent light. That requires a 3D LUT for an accurate transformation!

In the feature film industry (where I mostly work) we use 3D LUTs throughout the image pipeline, not just for converting/transforms, but for "viewing" and for applying/emulating "looks." For instance taking an image shot with a digital camera and applying a LUT of a certain film stock to that image to make it appear as film.