Vision

Color blindness simulator

See which of your colours stop being different for the roughly 8% of people who see colour differently.

No functioning green cones. Red and green collapse toward each other.

prevalenceabout 1% of menpublished matrix

Palette check

Normal
  • #c81e4a
  • #14804a
  • #b8730b
  • #0e8f8a
  • #ff5a1f
  • #3c4250
Deuteranopia
  • #7e7445
  • #736c4e
  • #9a890f
  • #767b8b
  • #b3a012
  • #3c4150

2 pairs become hard to tell apart

  • #c81e4a#14804a ΔE 106.8 → 10.1 same lightness too
  • #b8730b#ff5a1f ΔE 40.6 → 11.4 same lightness too

Image check

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01

What is actually happening

Normal colour vision uses three cone types, sensitive to roughly long, medium and short wavelengths. Colour is worked out from the ratio between their responses. Remove one, or shift its sensitivity toward another, and whole regions of colour space that used to produce different ratios now produce the same one.

So the effect is more specific than colours looking duller: particular pairs become the same colour. Under deuteranopia, a red and a green of similar lightness become one colour, rather than two colours that are slightly harder to tell apart.

Deuteranomaly (reduced rather than absent green sensitivity) is by far the most common form, and it is a spectrum. Someone with a mild case may never have been diagnosed and may simply find certain interfaces inexplicably annoying.

02

The pairs that cause the trouble

Any pair that differs mainly in hue while sharing a similar lightness is a candidate. In practice the repeat offenders are:

  • Red and green, which almost every status indicator uses.
  • Green and brown, common in charts and maps.
  • Blue and purple, as in link states and selected states.
  • Light green and yellow, as in "warning" versus "success" badges.
  • Mid grey and mid anything, as in disabled versus enabled.

The tool above reports these as ΔE distances: how far apart two colours are perceptually before the simulation, and after. A pair that starts at ΔE 40 and ends at ΔE 3 has effectively merged.

It also tells you whether the pair still differs in lightness. That distinction matters more than the colours: lightness survives every deficiency, so a red and a green that differ enough in lightness usually remain usable even when their hues collapse.

03

How to fix it properly

The instinct is to change the colours. Usually the better fix is to stop making colour carry the meaning on its own.

Add a redundant cue. Put a tick and a cross alongside green and red, the word "Error" next to the red border, a dashed line as well as a different colour in a chart, or a pattern fill on the bar. Once the meaning survives without hue, the colour choice becomes decoration rather than information.

Separate by lightness, not hue. If two things must be distinguished by colour alone, give them clearly different lightness values. Check the pair in the contrast checker. A ratio of 1.6 or more between the two means the difference survives when hue does not.

Do not rely on a colour-blind-safe palette alone. They help, but a palette that is distinguishable in isolation can still fail at small sizes, on thin strokes, or against a coloured background.

04

Where this tool stops

A simulation models cone response. It does not model perception, adaptation, context, or a lifetime of learning to read colour differently. Someone with deuteranomaly is often far better at distinguishing certain shades than this simulation implies, because they have spent their life attending to the cues that remain.

So do not use this to decide "how it looks to them". Use it for the narrow, checkable thing it is good at: finding pairs that carry meaning and stop being different. That failure is real and reproducible, so it is worth fixing.

Frequently asked questions

How accurate is this?

The dichromat transforms (protanopia, deuteranopia and tritanopia) are the published Machado, Oliveira and Fernandes matrices, the same ones Chrome uses for its vision emulation. The anomalous forms are interpolated toward those matrices rather than using the separate published severity tables, so treat them as indicative. No simulation reproduces anyone's actual experience of colour. Use this to find pairs that collapse, which is a real failure you can check.

Why does the simulation run on linear light?

Because the matrices are defined there. Several web tools apply them straight to the gamma-encoded bytes, which is quicker and visibly wrong in the shadows. ColorFinders converts to linear light, applies the transform, and converts back.

What should I actually change after using this?

Usually not the colours. The reliable fix is to stop relying on colour alone: add an icon, a label, a pattern or a position difference so the meaning survives without hue. Where you do change colours, separate them by lightness rather than by hue, because lightness survives every deficiency.

Which combinations cause the most trouble?

Red against green at similar lightness is the classic, and it is exactly what most status indicators use. Green against brown, blue against purple, and light green against yellow are the other frequent offenders. Any pair that differs mainly in hue and barely in lightness is a candidate.

How many people does this affect?

Roughly 1 in 12 men and 1 in 200 women, so about 8% of a typical audience. Deuteranomaly alone accounts for more than half of that.

Read the guide