ColorAptitude is a digital platform for professional colour competency assessment, training and certification. The platform is not built on assumptions or conventions, but on a specific corpus of peer-reviewed research into colour perception, psychophysics and observer qualification.
1. The competency model: discrimination, attribution, communication
The core of ColorAptitude is a 3×3 competency matrix: three colour dimensions (hue, lightness, chroma) crossed with three competency layers (discrimination, attribution, communication).
This model is based on the finding of the National Research Council (1981) that no single clinical test instrument can adequately predict the ability to recognise, name and communicate colour. The FM100, the Cambridge Colour Test (CCT) and the Colour Assessment and Diagnosis test (CAD) measure only discrimination — perceiving the fact that two stimuli differ from each other. Attribution (which property changed?) and communication (how do you name it correctly?) are measured by none of these instruments (Kotterink, 2026).
| Hue | Lightness | Chroma | |
|---|---|---|---|
| Discrimination | Can you see the difference? | Can you see the difference? | Can you see the difference? |
| Attribution | Which property changed? | Which property changed? | Which property changed? |
| Communication | Can you name it correctly? | Can you name it correctly? | Can you name it correctly? |
The 3×3 competency matrix: three colour dimensions × three competency layers = nine measurement points.
2. Stimulus design: OKLCH
The colour stimuli in ColorAptitude are generated in the OKLCH colour space (Ottosson, 2020). OKLCH is a perceptually uniform colour space, which means that equal numerical steps in OKLCH correspond to equal visually perceived colour differences. This is an essential requirement for a valid discrimination test: if the stimuli are not perceptually uniform, the difficulty levels are not comparable.
Existing free online tests (including colorlitelens.com and the X-Rite online hue test) use HSB or sRGB as colour space. HSB is not perceptually uniform — a ΔH of 20° in the red region feels visually different from a ΔH of 20° in the green region. This makes the stimuli incomparable and the scores unreliable to interpret.
All inter-stimulus distances throughout the ColorAptitude assessment — including the magnitude scaling module — are calculated using OKLCH-based perceptual distances. CIEDE2000 (Sharma et al., 2005) is referenced for cross-comparison with industry partners that report deviations in that metric, but it is not the basis of the ColorAptitude scoring pipeline.
3. Scoring model: FM100 error formula and TES
The scoring formula for the ordering assessments is based on the error model of Farnsworth (1957). For each movable chip the partial error score is calculated as:
|position(previous) − position(placed)| + |position(next) − position(placed)| − 2
The Total Error Score (TES) is the sum over all chips. A TES inversion maps this error score to a scale of 0–100 where higher is better, so that scores across different assessments are directly comparable.
For norm comparison, the TES values are transformed as √TES, in accordance with Kinnear and Sahraie (2002), who demonstrated that this transformation stabilises the age-related variance and yields a more linear norm distribution.
4. Age correction: Kinnear & Sahraie (2002)
Colour perception is age-dependent. Kinnear and Sahraie (2002) published the most extensive normative dataset for the FM100, based on 382 Ishihara-screened normal trichromats. The dataset contains TES means and 95th percentiles per year for ages 5–22 and per decade for 30–79.
Paramei and Oakley (2014) documented a two-phase course of decline in chromatic discrimination thresholds: gradual from age 30, accelerating after 60. The tritan axis (blue-yellow) declines earlier and more steeply than the protan/deutan axes (red-green).
ColorAptitude applies age correction to the hue ordering discrimination scores, where published FM100 norms are available per age decade. This makes the results of a 55-year-old comparable to the norms for that age group, rather than to an absolute scale based on the average score of 25-year-olds. Age correction for the remaining assessments will follow once sufficient normative data have been collected.
5. ASTM E1499-16 conformity
ASTM E1499-16 — Standard Guide for Selection, Evaluation, and Training of Observers — has been implemented as the design framework for ColorAptitude (American Society for Testing and Materials, 2016).
Specifically the following sections are implemented:
§6.3.2 — Chroma Threshold (2AFC adaptive staircase)
The Chroma Threshold Diagnostic implements a 2AFC forced-choice test with adaptive staircase, methodologically inspired by the principles of ASTM E1499 §6.3.2. The staircase converges on the participant's perceptual threshold for chroma discrimination.
§6.4 — Magnitude Scaling
The magnitude scaling assessment presents colour pairs and asks participants to estimate the perceived magnitude of the difference on a ratio scale, relative to an anchor pair with value 10. This is the first digital implementation of ASTM §6.4 (Kotterink, 2026).
§7.1.1 — Warmup observations
Every ordering assessment begins with an unscored warmup series, in accordance with the finding of Hovis et al. (1992) that 36% of colour-blind subjects make an error on the first attempt — an attention artefact, not a discrimination problem.
§8.1.1 — Session limits
Timing and movement counts are stored per session. The mini-scan is limited to 10 chips per dimension to prevent session-length fatigue.
6. Screen calibration — two levels
ASTM E1499-16 §5.3 warns against the use of uncalibrated digital displays as a substitute for validated physical tests. ColorAptitude addresses this via a two-tier calibration strategy.
Tier 1 — Software calibration (default)
A mandatory seven-step visual screen calibration validates gamma (γ 2.2), black level, white level, luminance, white point, colour gamut and colour balance. This eliminates the most gross screen deviations and is suitable for screening and education. Results are indicative. For formal observer-qualification under ASTM E1499, Tier 2 (hardware calibration) is required.
Tier 2 — Hardware calibration (organisations)
For compliance-grade observer qualification in accordance with ASTM E1499-16 §5.3, ColorAptitude offers an organisation package including Datacolor SpyderPro. The hardware colorimeter objectively verifies: D65 white point (xy 0.3127, 0.3290), γ 2.2, luminance in cd/m² and colour gamut. This eliminates the circular reasoning inherent in visual calibration — the visual system no longer validates the stimuli presented to that same system.
The certificate states which calibration level was used. Tier 2 certificates can be used as audit evidence for ISO 9001 and ASTM audits.
7. Validation status
ColorAptitude is in the proof-of-concept validation phase. Preliminary norm data are based on published FM100 norms (Kinnear & Sahraie, 2002). A structured norm data collection programme has been started via an ongoing reference population study.
Future work includes:
- Empirical norm determination per age decade and professional domain
- Bland-Altman test-retest analysis
- Convergent validation against FM100 and CCT scores
- Extension of the communication exercise with industry-specific colour notation systems (NCS, RAL, Munsell)
Key references
American Society for Testing and Materials. (2016). ASTM E1499-16: Standard Guide for the Selection, Evaluation, and Training of Observers. ASTM International.
Farnsworth, D. (1957). The Farnsworth-Munsell 100-Hue Test for the Examination of Color Discrimination (rev. ed.). Munsell Color Company.
He, J., Bex, P. J., & Skerswetat, J. (2023). Rapid measurement and machine-learning classification of colour vision deficiencies using the FInD Colour Test. medRxiv. doi:10.1101/2023.10.13.23296982
Hovis, J. K., Dolman, H., & Neumann, P. (1992). A clinical test to estimate chromatic thresholds. Clinical and Experimental Optometry, 75(4), 159–165.
Kinnear, P. R., & Sahraie, A. (2002). New Farnsworth-Munsell 100 hue test norms of normal observers for each year of age 5–22 and for age decades 30–70. British Journal of Ophthalmology, 86(12), 1408–1411.
Kotterink, M. (2026). A digital platform for professional colour competency: Assessment, training and certification. Stichting Xconea.
National Research Council. (1981). Procedures for Testing Color Vision: Report of Working Group 41. National Academy Press.
Ottosson, B. (2020). A perceptual color space for image processing. bottosson.github.io/posts/oklab
Paramei, G. V., & Oakley, B. (2014). Variation of color discrimination across the life span. Journal of the Optical Society of America A, 31(4), A375–A384.
Seshadri, J., Christensen, J., Lakshminarayanan, V., & Bassi, C. J. (2005). Evaluation of the new web-based ‘Colour Assessment and Diagnosis’ test. Optometry and Vision Science, 82(10), 882–885.
Sharma, G., Wu, W., & Dalal, E. N. (2005). The CIEDE2000 color-difference formula. Color Research & Application, 30(1), 21–30.
Verriest, G., Van Laethem, J., & Uvijls, A. (1982). A new assessment of the normal ranges of the Farnsworth-Munsell 100-Hue test scores. American Journal of Ophthalmology, 93(5), 635–642.
The full scientific paper is available via xconea.com. ASTM E1499-16 is available via astm.org.