ISO/DTR 26478

• Abstract:

  This document provides information related to the selection of skin tones for use in image capture tests of digital imaging devices 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 tone

• Status: Not Published
• 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: 5020 - FDIS ballot initiated: 2 months. Proof sent to secretariat
• Start Date: 21-Aug-2026
• Completion Date: 21-Aug-2026

Overview

ISO/DTR 26478: Digital Imaging - Skin Tone Representation for Use in Photographic Testing provides comprehensive guidance on the selection and use of skin tone patches for evaluating digital imaging devices, such as cameras. Developed by ISO/TC 42, this technical report targets inclusivity by ensuring photographic testing encompasses a broad range of human skin tones. The standard details the selection of representative colour patches and spectral reflectance data, supporting fair and effective testing procedures. This document responds to growing awareness of the importance of cross-cultural representation and aligns with global efforts to foster inclusivity in imaging standards.

Key Topics

• Inclusive Skin Tone Representation: The standard emphasizes the need to represent a wide variety of skin types in digital imaging tests, addressing both light and dark tones to mirror real-world diversity.
• Skin Tone Test Charts and Spectra: It offers detailed information on test charts commonly used for skin tone reproduction, such as the ColorChecker Classic, ColorChecker Digital SG, and several commercial and research-based skin tone scales (e.g., Fitzpatrick, L'Oréal, Monk skin tone).
• Spectral Reflectance Data: Guidance is provided on using measured skin tone spectral data-such as datasets from NIST and CIE-to inform the accurate creation and validation of skin patches for standardized testing.
• Validation Criteria: The standard discusses both technical (spectral and colorimetric accuracy) and perceptual validation by diverse human viewers, emphasizing the importance of perceived correctness and cross-cultural inclusivity rather than relying solely on instrument-based measurement.
• Applications in Test Design: Recommendations are given for selecting skin tone patches in test targets for digital image capture, archiving, and image permanence evaluation.

Applications

ISO/DTR 26478 is widely applicable wherever digital images of people are captured, reproduced, or evaluated. Key applications include:

• Photographic Device Testing: Manufacturers and testing laboratories can use the recommended skin tone patches and spectral data to evaluate digital cameras' color reproduction capabilities, ensuring devices accurately reflect diverse human subjects.
• Image Quality Assessment: Standards for assessing image quality, permanence, and color consistency benefit from the inclusion of representative skin tone data, enabling consistent and fair benchmarking across manufacturers and media.
• Development of Test Charts: Designers of photographic and printing test charts use this report to select and organize skin tone patches, ensuring inclusivity and technical relevancy in reference materials.
• Cross-disciplinary Use: While the primary audience is photography and imaging professionals, related industries such as cosmetics, healthcare, and machine learning-where accurate skin tone rendering is vital-can also apply these principles.
• Standardization Compliance: Organizations seeking to conform to ISO digital imaging and color measurement standards will find essential guidance for selecting skin tone representations aligned with international best practices.

Related Standards

ISO/DTR 26478 references and complements several key standards relevant to digital imaging and color accuracy. Notable related standards include:

• ISO 19093 - Photography - Digital cameras - Measuring low-light performance
• ISO 17321-1/2 - Graphic technology and photography - Colour characterisation of digital still cameras
• ISO 19264-1 - Photography - Archiving systems - Imaging systems quality analysis
• ISO/PAS 18940-1 - Imaging materials - Image permanence specification for indoor applications
• ISO/TS 21139-22 - Permanence and durability of commercial prints for backlit display
• ISO 18946 - Imaging materials - Reflection colour photographic prints - Humidity fastness testing
• ANSI CGATS/ISO 12641-1 - Graphic technology - Colour targets for input scanner calibration
• CIE 256:2025 - Human Skin Colour Database

These standards collectively support robust, fair, and reproducible digital imaging workflows, ensuring that skin tone representation is scientifically grounded and internationally recognized.

Keywords: ISO/DTR 26478, digital imaging standard, skin tone representation, test charts, spectral reflectance, color accuracy, photographic testing, inclusivity, ColorChecker, image quality assessment, ISO standards, color calibration, cross-cultural validation.

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Digital imaging — Skin tone
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Technical
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ISO/TC 42
Digital imaging — Skin tone
Secretariat: ANSI
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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
7 Spectral data corresponding to representative skin tone swatches . 14
8 Considerations .15
8.1 Considerations for scene-referred image capture standards . 15
8.2 Considerations for output-referred image evaluation standards . 15
8.3 Considerations for perceptual validation and cross-cultural inclusivity .16
Annex A (informative) Digital image capture standards including skin tones . 17
Annex B (informative) Image permanence and printing standards including skin tones .23
Annex C (informative) Reasons for differences between laboratory, in-situ and rendered image
surface colour measurements (including skin tone measurements).26 ®
Annex D (informative) Macbeth & Xrite ColorChecker comparison.30
Bibliography .32

iii
Foreword
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This document was prepared by Technical Committee ISO/TC 42, Photography
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.

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
FINAL DRAFT Technical Report ISO/DTR 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 WG 5. These standards are described in Annex B:
— ISO/PAS 18940-1:2023;
— 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. ISO 18944
is currently being revised to include skin tone patches which are consistent with ISO/PAS 18940-1 and
ISO 12647-7.
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 6.10.
6.2 ColorChecker classic test chart
The original design of the most widely used colour test chart was described in a 1976 publication.
1)
(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 Calibrate 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) in
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].
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
2)
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 Calibrate 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
3)
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 limit 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
® TM
6.7 PANTONE SkinTone guide
® TM 4)
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 .princeton .edu/ perla -color -palette/
Figure 9 — PERLA colour palette

6.9 Monk skin tone scale
The Monk skin tone scale, shown as swatches in Figure 10, is designed for machine learning applications. It
was developed by Dr. Ellis Monk at Harvard University to address the biases in the Fitzpatrick scale, which is
skewed towards lighter skin tones that are more UV sensitive. The 10 skin tones in the Monk skin tone scale
represent a diverse range of tones, while using a manageable number of patches. (See Reference [5]).
Figure 10 — Monk skin tone scale swatches
The Monk skin tone scale is often depicted using orbs, as shown in Figure 11. 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.
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
(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.
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 0
Monk 10 41 36 32 14,610 1,482 3,525
Some of the Monk scale CIELAB skin tone patch values lie outside the measured skin tone gamut.
(See Reference [15]). The three brightest patches are above an L* value of 90, which is beyond what a
photographic print on paper can achieve. These Monk L* values are higher than the L* values of most papers,
especially those without optical brighteners.
In addition, the Monk skin tones are significantly more yellow than natural skin tones and do not show the
red component from the hemoglobin in the blood flowing through the skin. The skin tones in this scale are
rendered for a display with a reference white point of 6 500 K. For such a cool reference white, it appears
that the tones need to be turned into “warmer” tones in order to be perceived as natural.
6.10 Colorimetric skin tone scale
The colorimetric skin tone scale (CST) was developed based on 2,517 colorimetric facial skin tone
[14]
measurements from US research volunteers belonging to different demographic groups .
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 Reference [14].
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
The authors reported that the colorimetric skin tone scale was more sensitive, consistent, and
colorimetrically accurate relative to the Monk skin tone scale.
7 Spectral data corresponding to representative skin tone swatches ®
Many of the Pantone skin colour patches show an excellent spectral match with the in-situ measured skin
reflectance data, as shown in Figure 13. 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 13 — 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
IE in-situ measurements, 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 variability and geometry.
To address this issue, every in-situ skin spectral reflectance was converted to spectral radiance as
illuminated by D50 and normalized by whatever factor produced the smallest sum of squared differences
®
when compared to each Pantone patch spectral reflectance, also illuminated by D50. Then, the in-situ –
® ®
Pantone pair with the smallest sum of squared difference was compared for each Pantone patch. This
removed the in-situ illumination quantity from the comparison.
8 Considerations
8.1 Considerations for scene-referred image capture standards
Most digital cameras do not fulfil the Luther-Maxwell-Ives condition, since their spectral sensitivities are
not linear combinations of the colour matching functions of the human visual system. In other words, these
cameras “see” colours differently than humans. As a result, two colour patches that look identical to humans
under one illumination (i.e. they are colourimetrically equal) will look different to most digital cameras
if the spectral reflectances of the two patches are not identical. This means that using a colour chart for
camera colour characterization will only produce accurate results if the colour patches on the chart are an
accurate spectral match to real world skin tones as well as to the colours of other natural objects.
TC 42 has not been able to identify any skin tone colour charts that completely fulfil these challenging
TM
spectral requirements. However, the Pantone® SkinTone guide includes patches using colourants
which closely match some insitu measured skin tones. This means that a calibration using the Pantone®
TM
SkinTone guide as a chart can produce reasonably accurate skin tone capture.
Since no chart can represent all real-world colours, characterizing colour cameras using a spectral approach
with a large number of suitable spectra can be more accurate. In this method, the spectral sensitivity of the
camera is measured, and the spectral distribution of the light source and the spectral data of representative
scene elements are used to calculate colour correction matrices or multidimensional lookup tables which
perform colour correction of the image data from the camera’s image sensor.
A database including 554 skin tone spectra, is available from Image Engineering at https:// image
-engineering .de/ library/ data -and -tools and can be used to ensure a good representation of all skin types.
8.2 Considerations for output-referred imag
...

ISO /TC 42
Secretariat: ANSI
Date: 2026-03-25xx
Digital imaging – — Skin tone representation for use in photographic
testing, including test charts and test spectra

All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication
may be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying,
or posting on the internet or an intranet, without prior written permission. Permission can be requested from either ISO
at the address below or ISO'sISO’s member body in the country of the requester.
ISO Copyright Officecopyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: + 41 22 749 01 11
Email:
E-mail: [e-mail]
Website: www.iso.org
Published in Switzerland.
ii
Contents
Foreword . iv
Introduction . v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Image capture standards . 3
4.1 General . 3
4.2 Printing and image permanence . 3
5 Skin tone spectra . 4
6 Test charts and colour palettes with skin tone patches. 6
6.1 General . 6
6.2 ColorChecker classic test chart . 6
6.3 ColorChecker digital SG test chart . 8
6.4 Fitzpatrick skin types . 8
6.5 L’Oréal skin type chart . 9
6.6 IT8 chart . 10
® TM
6.7 PANTONE SkinTone guide . 11
6.8 PERLA colour palette . 12
6.9 Monk skin tone scale . 13
6.10 Colorimetric skin tone scale . 15
7 Spectral data corresponding to representative skin tone swatches . 16
8 Considerations . 16
8.1 Considerations for scene-referred image capture standards . 16
8.2 Considerations for output-referred image evaluation standards . 17
8.3 Considerations for perceptual validation and cross-cultural inclusivity . 18
Annex A (informative) Digital image capture standards including skin tones . 19
Annex B (informative) Image permanence and printing standards including skin tones . 26
Annex C (informative) Reasons for differences between laboratory, in-situ and rendered image
surface colour measurements (including skin tone measurements) . 30 ®
Annex D (informative) Macbeth & Xrite ColorChecker comparison . 34
Bibliography . 36

iii
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out through
ISO technical committees. Each member body interested in a subject for which a technical committee has been
established has the right to be represented on that committee. International organizations, governmental and
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International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types of
ISO documentsdocument should be noted. This document was drafted in accordance with the editorial rules
of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawnISO draws attention to the possibility that some of the elementsimplementation of this
document may beinvolve the subjectuse of (a) patent(s). ISO takes no position concerning the evidence,
validity or applicability of any claimed patent rights in respect thereof. As of the date of publication of this
document, ISO had not received notice of (a) patent(s) which may be required to implement this document.
However, implementers are cautioned that this may not represent the latest information, which may be
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This document was prepared by Technical Committee ISO/TC 42, Photography
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.
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/TC42 – Photography,TC 42 has developed numerous standards which include colour patches or spectral
data intended to represent various skin tones. (See Reference [12][12] Wueller)) 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 TC42TC 42
standards would be inclusive and represent a broad range of skin types. This technical reportdocument
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.
., 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 Inequalityinequality) by providing
information related to the selection of an inclusive set of colour patches.
v
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
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO 22028-1, Photography and graphic technology — Extended colour encodings for digital image storage,
manipulation and interchange — Part 1: Architecture and requirements
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 terminologicalterminology 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 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
opto-electronic conversion function
OECF
relationship between the log of the input levels and the corresponding digital output levels for an opto-
electronic digital image capture system
3.2 3.3
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 3.4
photography
acquisition, processing, or reproduction of optically formed images using chemical or electronic technologies
3.4 3.5
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 3.6
skin tone
The 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 3.7
test chart
arrangement of test patterns designed to test particular aspects of an imaging system
3.7 3.8
test pattern
specified arrangement of spectral reflectance or transmittance characteristics used in measuring an image
quality attribute
4 Background
This report documents some of the work of an ISO/TC42 Ad Hoc Group (AHG) created in the fall of 2023 to
consider the test chart skin tone patches used in ISO/TC42 standards. One goal of this AHG was to provide
information for TC42 working groups to consider regarding the use of skin tone representations for ISO/TC42
related work. For example, when colour patches for skin tones are used in TC42 standards, it is important that
they be inclusive and represent a broad range of skin types. (See [12] Wueller)
The AHG reviewed all ISO standards developed by TC42 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.
54 Image capture standards
4.1 General
The following published ISO standards or technical reportsTechnical Reports developed by ISO/TC42TC 42
relate to digital image capture and include test patches or spectra intended to represent skin tones. These
standards are described in Annex Aannex A.:
— ISO 19093:2018 Photography — Digital cameras — Measuring low-light performance;
ISO 17321-1:2012 Graphic technology and photography — Colour characterisation of digital still cameras
(DSCs) — Part 1: Stimuli, metrology and test procedures
ISO/TR 17321-2:2012 Graphic technology and photography — Colour characterisation of digital still
cameras (DSCs) — Part 2: Considerations for determining scene analysis transforms
ISO 19264-1:2021 Photography — Archiving systems — Imaging systems quality analysis — Part 1:
Reflective originals
— 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][7]
McCamy.)).
5.14.2 Printing and image permanence
The following image permanence and printing standards or technical specifications were reviewed by experts
from WG 5. These standards are described in Annex Bannex B.:
ISO/PAS 18940-1:2023 Imaging materials — Image permanence specification of reflection photographic
prints for indoor applications — Part 1: Test methods
ISO/TS 21139-22:2023 Permanence and durability of commercial prints - Part 22: Backlit display in indoor
or shaded outdoor conditions - Light stability
ISO 18946:2023 Imaging materials — Reflection colour photographic prints — Method for testing humidity
fastness
— ISO/PAS 18940-1:2023;
— ISO/TS 21139-22:2023;
— ISO 18946:2023;
— ISO/TS 20791-2:2021 Photography — Photographic reflection prints - Part 2: Evaluation of colour variation
in printing;
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][7]
McCamy.)). 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 18944:2018 Imaging materials — Reflection colour photographic prints — Test print
construction and measurement 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. ISO
18944:2018 is currently being revised to include skin tone patches which are consistent with ISO /PAS 18940-
1 and ISO 12647-7.
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.
65 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][10] Wueller)). Examples of the relative radiance spectra of real skin tones
are shown in Figure 1Figure 1 below. (See Reference [11][11] Wueller)).
26478_ed1fig1.EPS
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] [3]
Institute of Standards and Technology (NIST), as described in Cooksey, et al. . See .
The text file posted at this URL was converted to Excel format, and the spectra are shown in Figure 2
(see Reference [2]Figure 2 below (See [2] Burns).). 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.
26478_ed1fig2a.EPS 26478_ed1fig2b.EPS

a)a)  NIST 100 reflectance spectra (250 to 1 400) nm b)b)  Visible wavelengths (400 to 700) nm
Key
X wavelength
Y reflectance
Figure 2 — a) NIST 100 reflectance spectra (250-1 400 nm), b) visible wavelengths (400-700 nm)
CIE Technical Committee 1-92 has developed and published a Human Skin Colour Database (CIE 256:2025)
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-
humanskincolourdatabase
[9][9] [13] [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
76 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 6.10below.
7.16.2 ColorChecker Classicclassic test chart
The original design of the most widely used colour test chart was described in a 1976 publication.
1 1)
(See Reference [7][7] McCamy).). 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 3Figure 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][7] McCamy).).

Macbeth ColorChecker, Gretag-Macbeth ColorChecker, X-rite ColorChecker, and Calibrate 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.
1)
Macbeth ColorChecker, Gretag-Macbeth ColorChecker, X-rite ColorChecker, and Calibrate 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.

26478_ed1fig3.EPS
Figure 3 — ColorChecker Classicclassic 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][1] Breneman. The
Kodak chart had 24 patches arranged in a (6 x× 4) grid. Each patch was produced by applying pigments to 2x2
inch(2 × 2) in 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]). See [1].
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 TC42/TC 42 standards described earlier in 4.14.1 and 4.24.2 that include dark skin and light skin
patches are based on the spectral reflectances of the original Macbeth ColorChecker described in
Reference [7]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 DAnnex D. It
shows that the spectral data in the TC42TC 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.
7.26.3 ColorChecker Digitaldigital SG test chart
2 2)
The ColorChecker Digitaldigital SG chart , , currently available from Calibrite, is shown in Figure 4Figure 4.
This test chart is A4-sized and features 140-patches designed for digital camera calibration and ICC Profile
determination.
26478_ed1fig4.EPS
Figure 4 — ColorChecker Digitaldigital SG test chart
The target includes the same 24 patches from the ColorChecker Color Rendition Chartcolour 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/
7.36.4 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][4] Fitzpatrick).).
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 Calibrate 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.
2)
The Calibrate 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.

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 5Figure 5. See https://www.newbeauty.com/how-to-use-fitzpatrick-
scale/
26478_ed1fig5.EPS
Figure 5 — Fitzpatrick Scale Classificationscale classification of 6 Skin Typesskin types
Although some research has interpreted the Fitzpatrick skin types as skin tone labels in machine learning
applications, this is not a recommended practice.
7.46.5 L’Oréal skin type chart
A more diverse skin tone representation, the 66-patch skin type chart shown in Figure 6Figure 6,, was
33)
developed by L'Oréal to enable matching skin tones to appropriate cosmetic products. (See Reference [6][6]
L’Oréal).). 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][8] Thong).).

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.
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.

26478_ed1fig6.EPS
Figure 6 — L'Oréal 66-patch skin type chart
The colour values of the L’OrealL’Oréal chart are not publicly available. The number of patches contained on
this chart limit its use as a calibration chart in some applications in photography and print.
7.56.6 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 Graphic technology - Color reflection target for input scanner calibration. Currently,
this standard is known as ANSI CGATS/ISO 12641-1:2018 Graphic technology - Prepress digital data exchange
- Colour targets for input scanner calibration - Part 1: Colour targets for input scanner calibration. The target
includes 264 colour patches in a grid of 22 columns x 12 rows, along with 24 grey patches, as shown in
Figure 7Figure 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 7Figure 7.
26478_ed1fig7.EPS
Figure 7 — IT8 Colour reflection target for input scanner calibration
® TM
7.66.7 PANTONE SkinTone guide
® TM 44)
The PANTONE SkinTone guide is a collection of 138 separate skin tone patches arranged in a fan, as
shown in Figure 8Figure 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

4 ® TM
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.
4) ® TM
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.

26478_ed1fig8.EPS
® TM
Figure 8 — PANTONE SkinTone guide
7.76.8 PERLA Color Palettecolour 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 colorcolour palette, shown in
Figure 9figure 9 below,, 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.princeton.edu/perla-color-palette/
26478_ed1fig9.EPS
Figure 9 — PERLA Color Palettecolour palette
7.86.9 Monk skin tone scale
The Monk skin tone scale, shown as swatches in Figure 10Figure 10,, is designed for machine learning
applications. It was developed by Dr. Ellis Monk at Harvard University to address the biases in the Fitzpatrick
scale, which is skewed towards lighter skin tones that are more UV sensitive. The 10 skin tones in the Monk
skin tone scale represent a diverse range of tones, while using a manageable number of patches.
(See Reference [5][5] Google).).
26478_ed1fig10.EPS
Figure 10 — Monk skin tone scale swatches
The Monk skin tone scale is often depicted using orbs, as shown in Figure 11Figure 11. 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.
26478_ed1fig11.EPS
Figure 11 — Monk skin tone scale orbs
The Monk skin tone scalerepresentation matched to each application class is intendeddescribed above: for
applications such as developing and testing face recognition algorithms. As a result, the Monk skin tone scale
is represented using rendered sRGB values which are designed to be displayed on a monitor. This means that
the Monk skin tone scale is in an sRGB output-referred image state, and the sRGB values represent output
workflows (rather than scene-referred image data,state workflows) as described in ISO 22028-1. The Monk
skin tone scale values, the values listed in Table 1 are appropriate; for printed-reference and spectral
applications, the Pantone physical swatches and corresponding spectroradiometric data are also provided as
LAB values, and boththe appropriate references; for applications requiring the full chromatic and dimensional
representation of human skin, the continuous reference orbs (Figure 11) are the primary representation.
The CIELAB values listed in Table 1 below.
It is believed that the LAB values were determinedcalculated by converting the rendered sRGB values to D65
XYZ with the display black point scaled to zero and then 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.
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 0
Monk 10 41 36 32 14,610 1,482 3,525
Some of the Monk scale CIELAB skin tone patch values lie outside the measured skin tone gamut.
(See Reference [15][15] Cook).). The three brightest patches are above an L* value of 90, which is beyond what
a photographic print on paper can achieve. These Monk L* values are higher than the L* values of most papers,
especially those without optical brighteners.
In addition, the Monk skin tones are significantly more yellow than natural skin tones and do not show the red
component from the hemoglobin in the blood flowing through the skin. The skin tones in this scale are
rendered for a display with a reference white point of 6 500 K. For such a cool reference white, it appears that
the tones need to be turned into “warmer” tones in order to be perceived as natural.
7.96.10 Colorimetric skin tone scale
The colorimetric skin tone scale (CST) was developed based on 2,517 colorimetric facial skin tone
[14][14]
measurements from US research volunteers belonging to different demographic groups .
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.
Hue and chromaticity are estimated as a function of L* using linear regression such that:

The colours shown in Figure 12Figure 12 and colour coordinates in Table 2Table 2 were computed using skin
[14]
tones measured by Reference [14] .
26478_ed1fig12.EPS
Figure 12 — Colorimetric skin tone scale
Table 2 — Colour coordinates of colorimetric skin tone scale
patchPatc L* a* b*
h
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
The authors reported that the colorimetric skin tone scale was more sensitive, consistent, and colorimetrically
accurate relative to the Monk skin tone scale.
87 Spectral data corresponding to representative skin tone swatches ®
Many of the Pantone skin colour patches show an excellent spectral match with the in-situ measured skin
reflectance data, as shown in Figure 13Figure 13. Such a spectral match has the additional benefit of providing
a colourimetric match under all types of light sources.
26478_ed1fig13a.EPS 26478_ed1fig13b.EPS

a)a)  Lightest and darkest patches b)b)  Medium dark patches
Key
X wavelength
Y reflectance ®
Figure 13 — Comparison of measured skin tones (solid lines) and Pan
...