ISO/TR 26478:2026

• Abstract:

  This document provides information related to the representation of skin tones for use in photographic testing in order to be inclusive and represent a broad range of skin types. This includes the selection of colour patches intended to represent skin tones and spectral reflectance data intended to represent skin tones.

• Status: Published
• Publication Date: 11-Nov-2026
• ICS: 37.040.99 - Other standards related to photography
• Technical Committee: ISO/TC 42 - Photography
• Drafting Committee: ISO/TC 42/WG 23 - Joint ISO/TC 42 - ISO/TC 130 - CIE WG: Extended colour encodings for digital image storage, manipulation and interchange
• Current Stage: 6060 - International Standard published
• Start Date: 12-Nov-2026
• Completion Date: 12-Nov-2026

ISO/TR 26478 is an ISO technical report on digital imaging and skin tone representation for photographic testing. It gives information for selecting skin-tone colour patches and spectral reflectance data so image capture tests can represent a broad range of skin types. The report is aimed at people working on cameras, image quality testing, test charts, and related photographic workflows.

What does ISO/TR 26478 specify?

ISO/TR 26478 provides guidance on how skin tones should be represented in photographic testing so the chosen references are inclusive and cover a broad range of skin types. It focuses on two practical things: colour patches that stand for skin tones, and spectral reflectance data that stand for skin tones.

The document is organized into scope, references, terms and definitions, image capture standards, skin tone spectra, test charts and colour palettes with skin tone patches, spectral data for representative swatches, and considerations. It then adds four informative annexes that compare existing ISO uses of skin-tone or brown patches and explain measurement differences.

Annex	What it covers
Annex A	Digital image capture standards including skin tones
Annex B	Image permanence and printing standards including skin tones
Annex C	Reasons laboratory, in-situ, and rendered surface colour measurements differ
Annex D	Macbeth and X-Rite ColorChecker comparison

What are the key requirements of ISO/TR 26478?

ISO/TR 26478 is an informative technical report, so its value is in selection guidance rather than pass-fail requirements. Its main message is that the skin-tone reference should match the test purpose: camera characterisation, print evaluation, output viewing, or perceptual validation.

Skin-tone references for image capture

Clause 4 points to existing ISO/TC 42 image-capture standards that already use skin-tone or skin-tone-like patches. In practice, this matters because many current camera test targets still rely on only two classic skin-tone patches from the ColorChecker lineage, which limits inclusivity.

Clause 8.1 explains that scene-referred camera work is best supported by spectral data and by a large set of representative skin-tone spectra when available. The report also notes that the Pantone SkinTone guide can be used when camera spectral sensitivities are not available, and that a subset of those patches can support scene analysis transforms, though with less accuracy than a spectral-sensitivity-based approach.

Test charts and colour palettes

Clause 6 reviews the main charts and palettes that already contain skin-tone representations. These include the ColorChecker Classic test chart, ColorChecker Digital SG, Fitzpatrick skin types, the L’Oréal skin type chart, the IT8 chart, the PANTONE SkinTone guide, the PERLA colour palette, the Monk skin tone scale, and the colorimetric skin tone scale.

In practice, the report helps a reader choose the right kind of reference for the job. For example, the Fitzpatrick skin types are not a colour scale, the L’Oréal chart is more inclusive because it varies in both lightness and hue, the PANTONE SkinTone guide is designed for printed viewing under D65, and the Monk and CST scales are aimed at machine learning and colourimetric annotation workflows.

Spectral data and validation

Clause 7 discusses spectral data for representative skin-tone swatches and shows that some Pantone skin-tone patches closely match measured skin reflectance. It also explains why laboratory measurements and in-situ skin measurements are not directly comparable without accounting for the illumination on the skin. For users, that means a good spectral match is useful, but the measurement context still has to be understood.

Clause 8.2 says output-referred skin-tone evaluation usually depends on the intended medium and viewing conditions, and that subjective methods such as ISO 20462 can be used. Clause 8.3 adds that a valid reference should be checked for perceptual validation, cross-cultural inclusivity, comparative discriminative validity, validation in use, and availability in multiple forms such as spectral data, sRGB, CIELAB, printed references, or continuous visual representations.

What terms does ISO/TR 26478 define?

• digital camera - A device with an image sensor that produces a digital signal representing a picture, which is the basic capture device discussed in the report.
• opto-electronic conversion function (OECF) - The relationship between input levels and digital output levels in an opto-electronic image capture system, used when characterising camera response.
• output-referred image state - An image state whose colour values are already rendered for a specified output device and viewing condition, which matters for display and print evaluation.
• scene-referred image state - An image state representing estimates of the colours in the original scene, which is the starting point for camera-based colour analysis.
• skin tone - The perceived colour of human skin, described here in CIELAB terms by lightness, hue, and chroma.
• test chart - An arrangement of test patterns used to evaluate an imaging system, such as a camera or scanner.
• test pattern - A specified arrangement of spectral reflectance or transmittance characteristics used to measure an image quality attribute.

Who uses ISO/TR 26478?

ISO/TR 26478 is mainly useful to ISO/TC 42 photographers’ standards groups, camera and camera-phone manufacturers, imaging-system evaluators, and colour-management engineers. It also helps people who design or assess test charts, ICC profiles, scene analysis transforms, and image permanence or print stability tests.

The report is relevant wherever human skin appears in the test subject matter, including digital cameras, scanners, displays, printers, and image-processing workflows. It is also useful to teams working on machine-learning skin-tone annotations, because it discusses the Monk skin tone scale and the colorimetric skin tone scale.

Which standards are used with ISO/TR 26478?

• ISO 22028-1 - Provides the architecture and requirements for extended colour encodings and the scene-referred/output-referred terminology used in the report.
• ISO 17321-1 - Gives stimuli, metrology, and test procedures for digital camera colour characterisation, including the use of test targets with skin-tone patches.
• ISO/TR 17321-2 - Describes approaches for determining scene analysis transforms and relates them to representative target spectra.
• ISO 19093 - Covers low-light performance measurement for digital cameras and uses a multi-purpose test chart with colour patches.
• ISO 19264-1 - Describes imaging-system quality analysis for reflective originals and includes colour reproduction and target use for scanners and cameras.
• ISO/TR 19263-1 - Gives best practices for digital image capture of cultural heritage material and describes colour patch elements used for profiling and colour accuracy checks.
• ISO/PAS 18940-1, ISO/TS 21139-22, ISO 18946, and ISO/TS 20791-2 - Show how skin-tone-like or brown patches are used in print permanence and printing evaluations.
• ISO 20462-1, ISO 20462-2, and ISO 20462-3 - Provide subjective methods for estimating image quality, which the report points to for output-referred skin-tone evaluation.

What does the ISO/TR 26478 document contain?

The document contains comparisons of existing skin-tone references used in ISO/TC 42 work, along with figures of test charts, skin-tone swatches, and spectral plots. It also includes tables of colour values for the Monk skin tone scale and the colorimetric skin tone scale, plus a table of skin-tone patch values used in ISO 19093.

Annex A compares digital image capture standards, Annex B compares image permanence and printing standards, Annex C explains why laboratory, in-situ, and rendered colour measurements differ, and Annex D compares Macbeth and X-Rite ColorChecker spectra. Those annexes are useful when deciding whether a patch set is a spectral match, a colourimetric match, or simply a practical test target for a specific workflow.

Technical
Report
ISO/TR 26478
First edition
Digital imaging — Skin tone
2026-11
representation for use in
photographic testing, including test
charts and test spectra
Imagerie numérique — Représentation des carnations pour
utilisation dans les essais photographiques, y compris les mires et
les analyses spectrales
Reference number
© ISO 2026
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ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Image capture standards . 2
4.1 General .2
4.2 Printing and image permanence .3
5 Skin tone spectra . 3
6 Test charts and colour palettes with skin tone patches . 5
6.1 General .5
6.2 ColorChecker classic test chart .5
6.3 ColorChecker digital SG test chart .6
6.4 Fitzpatrick skin types .7
6.5 L’Oréal skin type chart .8
6.6 IT8 chart .9
® TM
6.7 PANTONE SkinTone Guide .10
6.8 PERLA colour palette .11
6.9 Monk skin tone scale . 12
6.10 Colorimetric skin tone scale . 13
6.11 SkinTone Checker .14
7 Spectral data corresponding to representative skin tone swatches .15
8 Considerations .16
8.1 Considerations for scene-referred image capture standards .16
8.2 Considerations for output-referred image evaluation standards .16
8.3 Considerations for perceptual validation and cross-cultural inclusivity .17
Annex A (informative) Digital image capture standards including skin tones .18
Annex B (informative) Image permanence and printing standards including skin tones .24
Annex C (informative) Reasons for differences between laboratory, in-situ and rendered image
surface colour measurements (including skin tone measurements).27 ®
Annex D (informative) Macbeth & Xrite ColorChecker comparison.31
Bibliography .33

iii
Foreword
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iv
Introduction
Photography is widely used to depict a wide range of human subjects, and thus a wide range of skin tones.
It is important that photographic systems appropriately represent and reproduce this wide range of skin
tones.
ISO/TC 42 has developed numerous standards which include colour patches or spectral data intended to
represent various skin tones. (See Reference [12]) These include standards for characterizing digital
cameras and for image permanence.
This report documents some of the work of an ISO/TC 42 Ad Hoc Group (AHG) created in the fall of 2023
to consider the test chart skin tone patches used in ISO/TC 42 standards. One goal of this AHG was to
provide information for TC 42 working groups to consider regarding the use of skin tone representations for
ISO/TC 42 related work. For example, when colour patches for skin tones are used in TC 42 standards, it is
important that they be inclusive and represent a broad range of skin types. (See Reference [12].)
The AHG reviewed all ISO standards developed by TC 42 and identified eight relevant documents which
include patches or spectra that could be considered to represent skin tones. The relevant image capture-
related standards and technical reports are listed in 4.1 and discussed in Annex A, and the relevant image
permanence and printing related standards and technical reports are listed in 4.2 and discussed in Annex B.
Ideally, the colour patches and spectral reflectance data intended to represent skin tones in TC 42 standards
would be inclusive and represent a broad range of skin types. This document provides information which
is helpful when selecting skin tones for use in image capture testing of digital imaging devices (e.g. digital
cameras), specifically test charts which include skin tone patches and test spectra which represent skin
tones. It also provides links to spectral reflectance data intended to represent a broad range of skin types.
The validity of a set of reference skin tones for photographic testing depends on its validation against criteria
appropriate for the photographic-imaging application. For photographic systems that capture and reproduce
images for viewing by humans, these criteria are not limited to spectral and colorimetric accuracy, which are
necessary for spectral-domain applications but not sufficient for applications in which the reproduced image
is judged perceptually by diverse human viewers across diverse populations of subjects. For applications in
photographic testing of skin tone reproduction, additional relevant criteria include perceptual validation
across diverse perceivers, cross-cultural inclusivity in the populations against which perceptual validation
has been established, comparative discriminative validity against alternative references in independent
evaluation, and documented validation in use.
This report supports UN Sustainable Development Goal SDG 10 (Reduced inequality) by providing
information related to the selection of an inclusive set of colour patches.

v
Technical Report ISO/TR 26478:2026(en)
Digital imaging — Skin tone representation for use in
photographic testing, including test charts and test spectra
1 Scope
This document provides information related to the representation of skin tones for use in photographic
testing in order to be inclusive and represent a broad range of skin types. This includes the selection of
colour patches intended to represent skin tones and spectral reflectance data intended to represent skin
tones.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1
digital camera
device which incorporates an image sensor and produces a digital signal representing a picture
Note 1 to entry: A digital camera is typically a portable, hand-held device. The digital signal is usually recorded on a
removable or an internal memory.
3.2
output-referred image state
image state associated with image data that represents the colour-space coordinates of the elements of an
image that has undergone colour-rendering appropriate for a specified real or virtual output device and
viewing conditions
Note 1 to entry: When the phrase “output-referred” is used as a qualifier to an object, it implies that the object is in
an output-referred image state. For example, output-referred image data are image data in an output-referred image
state.
Note 2 to entry: Output-referred image data are referred to the specified output device and viewing conditions. A
single scene can be colour-rendered to a variety of output-referred representations depending on the anticipated
output-viewing conditions, media limitations, and/or artistic intents.
Note 3 to entry: Output-referred image data may become the starting point for a subsequent reproduction process.
For example, sRGB output-referred image data are frequently considered to be the starting point for the colour re-
rendering performed by a printer designed to receive sRGB image data.
3.3
photography
acquisition, processing, or reproduction of optically formed images using chemical or electronic technologies

3.4
scene-referred image state
image state associated with image data that represents estimates of the colour-space coordinates of the
elements of a scene
Note 1 to entry: When the phrase “scene-referred” is used as a qualifier to an object, it implies that the object is in a
scene-referred image state. For example, scene-referred image data are image data in a scene-referred image state.
Note 2 to entry: Scene-referred image data can be determined from raw digital camera image data before colour-
rendering is performed. Generally, digital cameras do not write scene-referred image data in image files, but some
may do so in a special mode intended for this purpose. Typically, digital cameras write standard output-referred image
data where colour-rendering has already been performed.
Note 3 to entry: Scene-referred image data typically represent relative scene colorimetry estimates. Absolute scene
colorimetry estimates may be calculated using a scaling factor. The scaling factor can be derived from additional
information such as the image OECF, FNumber or ApertureValue, and ExposureTime or ShutterSpeedValue tags.
Note 4 to entry: Scene-referred image data may contain inaccuracies due to the dynamic range limitations of the
capture device, noise from various sources, quantization, optical blurring and flare that are not corrected for, and
colour analysis errors due to capture device metamerism. In some cases, these sources of inaccuracy can be significant.
Note 5 to entry: The transformation from raw digital camera image data to scene-referred image data depends on the
relative adopted whites selected for the scene and the colour space used to encode the image data. If the chosen scene
adopted white is inappropriate, additional errors will be introduced into the scene-referred image data. These errors
may be correctable if the transformation used to produce the scene-referred image data are known and the colour
encoding used for the incorrect scene-referred image data has adequate precision and dynamic range.
Note 6 to entry: The scene may correspond to an actual view of the natural world or may be a computer-generated
virtual scene simulating such a view. It may also correspond to a modified scene determined by applying modifications
to an original scene to produce some different desired scene. Any such scene modifications should leave the image in a
scene-referred image state and should be done in the context of an expected colour-rendering transform.
3.5
skin tone
perceived colour of the surface of human skin
Note 1 to entry: A colour is expressed by the CIELAB colour space and characterized by lightness, hue, and chroma.
3.6
test chart
arrangement of test patterns designed to test particular aspects of an imaging system
3.7
test pattern
specified arrangement of spectral reflectance or transmittance characteristics used in measuring an image
quality attribute
4 Image capture standards
4.1 General
The following published ISO standards or Technical Reports developed by ISO/TC 42 relate to digital image
capture and include test patches or spectra intended to represent skin tones. These standards are described
in Annex A:
— ISO 19093:2018;
— ISO 17321-1:2012;
— ISO/TR 17321-2:2012;
— ISO/TR 19263-1:2017;
— ISO 19264-1.
Except for ISO 19093, these four documents use only two skin tone patches, a “dark skin” patch and a “light
skin” patch, from the ColorChecker colour rendition chart first defined in 1976. (See Reference [7]).
4.2 Printing and image permanence
The following image permanence and printing standards or technical specifications were reviewed by
experts from ISO/TC 42. These standards are described in Annex B:
— ISO/PAS 18940-1:2025;
— ISO/TS 21139-22:2023;
— ISO 18946:2023;
— ISO/TS 20791-2:2021;
One of these documents uses only two relevant patches, a lighter patch and a darker patch similar to those
defined for the original Macbeth ColorChecker test chart in 1976 as discussed above. (See Reference [7]).
Two more recent standards documents use the same two patches along with a third, darker brown patch.
The fourth document uses a total of 6 different light brown patches, intended to represent brownish colours
from many origins, such as landscape, leather, fur, but no dark brown patches.
In addition, ISO 18944 specifies requirements and recommendations for the digital test file content used to
generate target prints for image stability testing of reflection colour photographic prints.
The image permanence test targets defined in the standards described above were designed to cover the
printed colour space in general and are not intended to spectrally reproduce any specific natural colours
such as skin tones, blue sky or the colours of other natural objects. Photographic prints are based on a
limited number of pigments or dyes and therefore cannot spectrally match the wide range of colours of the
natural world but typically provide metameric matches. Therefore, a typical set of test patches for image
permanence contains single and mixed colorant patches to study the stability of the colorants separately or
in combination. These test targets have been validated by inter-laboratory comparison tests and have been
used for many years, providing a database of comparable permanence data for contemporary and historical
photographic material. If a permanence test is developed to specifically probe colour permanence of skin
tones, this report can provide relevant information regarding how to select such patches.
5 Skin tone spectra
A large percentage of photographs depict at least one person, and people are very sensitive to skin tone
reproduction errors in photography, so properly capturing and reproducing a diverse range of skin tones is
very important. (See Reference [10]). Examples of the relative radiance spectra of real skin tones are shown
in Figure 1. (See Reference [11]).

Key
X wavelength
Y relative radiances
Figure 1 — Examples of the relative radiance spectra of real skin tones
In addition, a set of 100 spectral measurements of human skin reflectance is available from the US National
[3]
Institute of Standards and Technology (NIST), as described in Cooksey, et al. .
The text file posted at this URL was converted to Excel format, and the spectra are shown in Figure 2
(see Reference [2]). Note that the spectral reflectance values range between 250 nm and 2 500 nm, in 3 nm
intervals. The wide wavelength range of the posted data was based on a range of potential uses, including
medical applications, that are beyond our area of focus.
a) NIST 100 reflectance spectra (250 to b)  Visible wavelengths (400 to 700) nm
1 400) nm
Key
X wavelength
Y reflectance
Figure 2 — NIST 100 reflectance spectra
CIE Technical Committee 1-92 has developed and published a Human Skin Colour Database (CIE 256) which
provides valuable data for research and applications related to skin colour measurement. This database
is available at: https:// www .cie .co .at/ publications/ measuring -skin -colour/ dataset1 -hum anskincolo
urdatabase
[9] [13]
In addition, skin tone spectral data has been reported by Wang, et. al and Xiao, et. al. Kaida Xiao has
published a version of the skin tone database at https:// www .kaidaxiao .co .uk/ about -1
6 Test charts and colour palettes with skin tone patches
6.1 General
Over the last fifty years, various colour test charts and colour palettes have been developed which include
patches intended to represent skin tones. These palettes serve different purposes. Some are designed for
medical use, some for cosmetics, and others to represent skin tones in print, display and image capture.
These charts and palettes are described in 6.2 to 6.11.
6.2 ColorChecker classic test chart
The original design of the most widely used colour test chart was described in a 1976 publication.
(See Reference [7]). The original name for this test chart was the “Macbeth ColorChecker”, which was
also referred to as the “Macbeth chart”. The current version of the test chart, now known as the Calibrite
ColorChecker Classic test chart, is shown in Figure 3. The 24 patches are surrounded by a black border and
include 6 patches in a grey lightness scale and saturated red, green, blue, cyan, magenta and yellow patches
in the two bottom rows of the chart. The original spectral reflectances of the colour patches in the top two
rows were chosen to approximate natural objects such as blue sky and green foliage.
The two colour patches in the upper left were intended to represent dark skin and light skin. The designers
of the original Macbeth ColorChecker test chart contended that the lightest human skin being photographed
is practically white, due to the use of talcum powder, while the darkest human skin is practically black, and
that both have nearly uniform spectral reflectances. They also contended that the characteristic spectrum
of human skin is primarily due to absorption by melanin and hemoglobin, such that the spectra for all types
of human skin form a continuous homologous series. The medium light skin and medium dark skin patches
were selected to test the ability of systems to reproduce the colour associated with this typical spectrum at
two different exposure levels. (See Reference [7]).
1) Macbeth ColorChecker, Gretag-Macbeth ColorChecker, X-rite ColorChecker, and Calibrite ColorChecker Classic are
examples of commercially available products. This information is given for the convenience of users of this document and
does not constitute an endorsement by ISO of this product.

Figure 3 — ColorChecker classic test chart
The selection and arrangement of colour patches in the Macbeth ColorChecker was based on an earlier colour
chart developed by Kodak Research Labs, which was reported in 1957. See Reference [1]. The Kodak chart
had 24 patches arranged in a (6 × 4) grid. Each patch was produced by applying pigments to (2 × 2) inch
pieces of cover glass which were held in a wooden frame. The chart included six neutral patches (including
a titanium white patch with 78 % reflectance and an ivory black patch with 0,22 % reflectance), nine highly
saturated colours, and several “familiar” colours including foliage, blue sky, and flesh. While it included only
a single “flesh” patch (produced using a combination of cadmium red, strontium yellow, ultramarine blue,
and titanium white pigments with 32 % reflectance), it also included a “brown” patch (produced using burnt
umber, burnt sienna, yellow ochre, and zinc oxide with 2,7 % reflectance), see Reference [1].
NOTE The decimal sign is a comma in ISO standards.
In 1997, the Gretag Color Control System Division merged with the Macbeth division of Kollmorgen
Instruments to form Gretag-Macbeth, which sold the similar Gretag-Macbeth ColorChecker chart. In
2006, X-Rite acquired the holding company which owned Gretag-Macbeth and began selling the X-rite
ColorChecker. In 2021, X-Rite photo and video products were transferred to a new company named Calibrite,
which currently sells the Calibrite ColorChecker Classic test chart.
The ISO/TC 42 standards described earlier in 4.1 and 4.2 that include dark skin and light skin patches
are based on the spectral reflectances of the original Macbeth ColorChecker described in Reference [7].
A comparison of this original ColorChecker chart and an X-Rite ColorChecker chart was made using a
SpectraScan PR-740 Spectroradiometer. The data is provided in Annex D. It shows that the spectral data in
the TC 42 standards provides a reasonably accurate representation of the original Macbeth ColorChecker
test chart. However, several colour patches on the X-Rite ColorChecker are substantially different from
the ISO data and the original Macbeth ColorChecker test chart. In particular, Patches 1 (dark skin), 3 (blue
sky), 4 (foliage), 5 (blue flower), 8 (purplish blue), and 13 (blue) of the X-Rite ColorChecker are significantly
different than the original Macbeth ColorChecker test chart. While the original test chart appears to mimic
these items spectrally, the X-Rite ColorChecker test chart seems to only mimic them colorimetrically. Patches
2 (light skin), 6 (bluish green), 7 (orange), 10 (purple), 14 (green), and 17 (magenta), are slightly different,
while the remaining colour patches are essentially the same.
6.3 ColorChecker digital SG test chart
The ColorChecker digital SG chart, currently available from Calibrite, is shown in Figure 4. This test chart
is A4-sized and features 140 patches designed for digital camera calibration and ICC Profile determination.
2) The Calibrite ColorChecker Digital SG chart is an example of a commercially available product. This information is
given for the convenience of users of this document and does not constitute an endorsement by ISO of this product.

Figure 4 — ColorChecker digital SG test chart
The target includes the same 24 patches from the ColorChecker colour rendition chart, including the light
skin and dark skin patches. It also includes 14 additional skin tone patches. The outer edge of the test chart
is composed of white, black and neutral patches, which can be used to assess the uniformity of the lighting.
This test chart is designed to be used with Calibrite PROFILER software. See https:// calibrite .com/ us/
product/ colorchecker -digital -sg/
6.4 Fitzpatrick skin types
The Fitzpatrick skin types were developed by American dermatologist Thomas Fitzpatrick in 1975, to
estimate the response of different skin types to ultraviolet (UV) light. Fitzpatrick skin types classify human
skin based on how the skin responds to UV exposure according to six phototypes which were determined
by responses to survey questions. It originally included only the first four skin tones and was expanded to
include the two darker tones in 1988. (See Reference [4]).
The Fitzpatrick skin type is widely used for skin phototyping, based on a person's tendency to sunburn and
ability to tan, which are correlated to skin melanin content and therefore skin tone. The Fitzpatrick skin
types were not designed to classify skin tones, and no standard relationship exists between Fitzpatrick skin
types and skin tones.
The Fitzpatrick skin type was not intended to be a colour scale, but it has been treated as such by some
dermatologists, as depicted in Figure 5. See https:// www .newbeauty .com/ how -to -use -fitzpatrick -scale/

Figure 5 — Fitzpatrick scale classification of 6 skin types
Although some research has interpreted the Fitzpatrick skin types as skin tone labels in machine learning
applications, this is not a recommended practice.
6.5 L’Oréal skin type chart
A more diverse skin tone representation, the 66-patch skin type chart shown in Figure 6, was developed
by L'Oréal to enable matching skin tones to appropriate cosmetic products. (See Reference [6]). The L'Oréal
chart shows skin tone patches with variations in two dimensions: skin lightness on the x-axis, and skin hue
on the y-axis. Representing this two-dimensional variation in skin tones is more inclusive than a single
lightness-darkness gradient. (See Reference [8]).
3) The L'Oréal skin type chart is an example of a commercially available product. This information is given for the
convenience of users of this document and does not constitute an endorsement by ISO of this product.

Figure 6 — L'Oréal 66-patch skin type chart
The colour values of the L’Oréal chart are not publicly available. The number of patches contained on this
chart limits its use as a calibration chart in some applications in photography and print.
6.6 IT8 chart
A colour rendition test chart, commonly known as the “IT8 chart”, was first standardized in 1993 as ANSI
standard IT8.7/2 - 1993. Currently, this standard is known as ANSI CGATS/ISO 12641-1:2018. The target
includes 264 colour patches in a grid of 22 columns x 12 rows, along with 24 grey patches, as shown in
Figure 7. It enables a graphic arts colour input scanner to be calibrated for the dye set used to create the
target.
The IT8.7/2 standard does not specify any colour patches that are intended to represent skin tones. However,
the colours in columns 20 through 22 are not specified in the standard and can be any colours chosen by the
chart manufacturer. Some manufacturers have decided to include colour patches representing skin tones, as
shown in column 22 of Figure 7.

Figure 7 — IT8 Colour reflection target for input scanner calibration
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6.7 PANTONE SkinTone Guide
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The PANTONE SkinTone Guide is a collection of 138 separate skin tone patches arranged in a fan, as
shown in Figure 8. Digital values for each patch are available. The colour of each patch is identified by a
unique Pantone Number which represents both the tone and the “undertone”, which is a value used by ®
PANTONE that reflects the hue of a skin tone on a red-yellow axis. The guide is designed for representing
skin tones in print, to be viewed using D65 (Daylight 6 500 K) illumination. It is said to have been “created
by scientifically measuring thousands of actual skin tones across the full spectrum of human skin types”
and “specially formulated to be the closest physical representations” of skin colours, that is to attempt a
spectral match between printed ink and measured skin tone.
See: https:// www .pantone .com/ products/ fashion -home -interiors/ skintone -guide
® TM
4) The PANTONE SkinTone guide is an example of a commercially available product. This information is given for
the convenience of users of this document and does not constitute an endorsement by ISO of this product.

® TM
Figure 8 — PANTONE SkinTone Guide
6.8 PERLA colour palette
The Project on Ethnicity and Race in Latin America (PERLA) was formed in 2008 to empirically examine race
and ethnicity across Latin America. The 11 colour patches in the PERLA colour palette, shown in Figure 9,
came from internet photographs to cover the range of colours found in Latin American survey respondents.
The methods for selecting the colour patches and their colour coordinates are not publicly available.
See: https:// perla .soc .ucsb .edu/ data/ color -palette
Figure 9 — PERLA colour palette

6.9 Monk skin tone scale
The Monk Skin Tone Scale (MST) is a 10-point, perception-based reference scale for human skin tone
variation, developed by Dr. Ellis Monk at Harvard University. (See Reference [5]). The MST is provided as a
multi-representation reference standard — continuous reference orbs, sRGB swatches with corresponding
CIELAB values, spectroradiometric measurements, and physical printed swatches produced in partnership
with Pantone Color Institute — to support applications across photographic testing, machine-learning
fairness evaluation, industrial colour management, clinical device performance evaluation, and biometric
performance testing.
Figure 10 — Monk skin tone scale swatches
The multi-representation architecture of the MST is a design choice that follows from the breadth of
applications it supports: a) continuous reference orbs (see Figure 11) are the primary visual representation
and depict the dimensional and chromatic variation of human skin including the contribution of the
hemoglobin chromophore in cutaneous blood flow. The orbs depict how each skin tone may appear in
both the real world and in images. This is a helpful reminder that a person's skin does not appear to be a
single, uniform colour. Rather, it can exhibit a range of shades across the complex surfaces that comprise a
person’s face and body; b) flat sRGB swatches and corresponding CIELAB values (see Figure 10 and Table 1)
are derived representations for applications requiring categorical reference patches in sRGB workflows,
including machine-learning fairness evaluation; c) physical printed reference swatches produced in
partnership with Pantone Color Institute provide print-referenced materials for use in photographic test
chart construction and printed-media evaluation; and d) spectroradiometric measurements of the 10
reference points are available for spectral applications including pulse oximeter calibration and camera
spectral characterization.
Figure 11 — Monk skin tone scale orbs
The representation matched to each application class is described above: for sRGB output-referred image
state workflows (rather than scene-referred image state workflows) as described in ISO 22028-1, the values
listed in Table 1 are appropriate; for printed-reference and spectral applications, the Pantone physical
swatches and corresponding spectroradiometric data are the appropriate references; for applications
requiring the full chromatic and dimensional representation of human skin, the continuous reference orbs
(see Figure 11) are the primary representation.
The CIELAB values listed in Table 1 were calculated by converting the rendered sRGB values to D65 XYZ
with the display black point scaled to zero and using D65 as the white point for the CIELAB calculations

(with no chromatic adaptation transform). This conversion supports display-referred (i.e., output-referred)
sRGB workflows. The CIELAB values in Table 1 do not include the reference veiling glare luminance of
0,2 cd/m² specified in IEC 61966-2-1; the display black point was scaled to zero as noted above.
Table 1 — sRGB and CIELAB values for the Monk scale
Patch sRGB R sRGB G sRGB B CIELAB L* CIELAB a* CIELAB b*
Monk 01 246 237 228 94,211 1,503 5,422
Monk 02 243 231 219 92,275 2,061 7,280
Monk 03 247 234 208 93,091 0,216 14,205
Monk 04 234 218 186 87,573 0,459 17,748
Monk 05 215 189 150 77,902 3,471 23,136
Monk 06 160 126 86 55,142 7,783 26,740
Monk 07 130 92 67 42,470 12,325 20,530
Monk 08 96 65 52 30,678 11,667 13,335
Monk 09 58 49 42 21,069 2,69 5,964
Monk 10 41 36 32 14,610 1,482 3,525
The sRGB swatches and corresponding CIELAB values in Table 1 are display-rendered representations
intended for sRGB workflow applications such as machine-learning fairness evaluation. The L* values for
the three lightest reference patches in Table 1 (above L* = 90) reflect the rendered sRGB representation
chosen to maintain perceptual contrast across the 10 reference points in display-referred workflows. These
three patches have L* values higher than the L* values of most photographic papers, especially those without
optical brighteners.
For applications requiring the full chromatic and dimensional representation of human skin — including the
contribution of the hemoglobin chromophore in cutaneous blood flow and the variation of tone across the
complex surfaces of the face and body — the continuous reference orbs (see Figure 11) and the associated
spectroradiometric data serve as the references.
The Monk skin tone scale was validated through a large-scale empirical human-perception study across
multiple geographic regions using diverse global observers (See Reference [32]). The validation methodology
centred on human perception of skin tone across geographies, ethnicities, and cultural contexts rather
than reflecting the assumptions of a single reference population. Printed test charts reproducing the MST
reference points have been validated against photographs of human subjects spanning the scale (See
Reference [33].
Physical printed reference swatches of the MST reference points 1–10 have been produced in partnership
with the Pantone® Color Institute. Pantone formulated new pigments specifically for the MST reference
points. Spectroradiometric measurements of the MST reference points are available for use in spectral
applications including pulse oximeter calibration, biometric imaging, photographic colour management,
and camera spectral characterization. The MST has been adopted in standardized applications at scale:
it is incorporated in ISO 80601-2-61:2025, is recommended in U.S. FDA draft guidance for pulse oximeter
performance evaluation (2025) and is referenced in ISO/IEC 19795-10.
6.10 Colorimetric skin tone scale
The colorimetric skin tone scale (CST) was developed based on 2,517 colorimetric facial skin tone
measurements from US research volunteers belonging to different demographic groups (See References [14]
[15].
The CST scale provides methods to create skin tone patches based on a set of observed skin tone values. The
scale is created by estimating hue and chromaticity at evenly spaced increments of L* values from 20 to 70.
The colours shown in Figure 12 and colour coordinates in Table 2 were computed using skin tones measured
by References [14][15].
Figure 12 — Colorimetric skin tone scale
Table 2 — Colour coordinates of colorimetric skin tone scale
Patch L* a* b*
1 70,00 6,07 4,70
2 64,44 11,02 9,26
3 58,89 14,44 13,06
4 53,33 16,45 15,94
5 47,78 17,20 17,74
6 42,22 16,79 18,35
7 36,67 15,34 17,66
8 31,11 12,93 15,62
9 25,56 9,65 12,16
10 20,00 5,55 7,26
6.11 SkinTone Checker
The SkinTone Checker shown in Figure 13 includes the 138 skin tone patches from the PANTONE SkinTone
Guide described in 6.7, along with the 24 patches of the ColorChecker classic test chart described in 6.2.
5) The SkinTone Checker is an example of a commercially available product. This information is given for the convenience
of users of this document and does not constitute an endorsement by ISO of this product.

Figure 13 — Skin tone checker test chart
The SkinTone Checker was developed by Image Engineering. See https:// www .image -engineering .de/ en/
products/ test -charts/ te300
7 Spectral data corresponding to representative skin tone swatches ®
Some of the Pantone skin colour patches show an excellent spectral match with the in-situ measured skin
reflectance data, as shown in Figure 14. Such a spectral match has the additional benefit of providing a
colourimetric match under all types of light sources.
a)  Lightest and darkest patches b)  Medium dark patches
Key
X wavelength
Y reflectance ®
Figure 14 — Comparison of measured skin tones (solid lines) and Pantone patches (dashed lines)
However, as discussed in Annex C, it can be difficult to compare patch measurements from a lab with in-situ
measurements because the illumination falling on the skin for the in-situ measurements is not precisely ®
known. To verify that the Pantone patches are good simulations of scene skin spectra, it is necessary to
estimate what would have been the diffuse white reference for the in-situ measurements. In the case of the
in-situ measurements shown in Figure 1, a diffuse white reference calibration disc was measured, and an

image captured of the scene, for each skin tone spectral radiance measurement. Furthermore, efforts were
made to avoid skin illumination conditions where substantial parts of the skin illumination came from light
reflected from coloured objects. The assumption was then made that the white reference disk measurement
provided an accurate measurement of the skin illumination spectral characteristics, for the calculation of
the in-situ skin spectral reflectances. Making this assumption does not provide a complete description of the
in-situ skin illumination, however, because the illumination quantity remains unknown. There was no way
to estimate the quantity of the illumination on the skin in the scene given that the skin samples measured
occurred with different scene content, with different scene illumination
...