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Deuteranopia Color Blindness Simulator

Free

See how your colors look to users with deuteranopia (red-green color blindness). Upload an image or enter a color. Free, browser-based.

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Settings guide

Types of red-green color blindness:

ConditionSeverityPrevalence (male)What changes
DeuteranomalyMild–moderate5%M-cones present but shifted — reduced green sensitivity
DeuteranopiaSevere1%M-cones absent — red and green both appear as yellow-brown
ProtanomalyMild–moderate1%L-cones shifted — reduced red sensitivity
ProtanopiaSevere1%L-cones absent — red appears very dark; more severe than deuteranopia

Designing for red-green color blindness:

  • ·Never use red/green as the only differentiator for status, success/error, or chart series
  • ·Add shape, icon, or text labels alongside color coding — a ✓ and ✗ alongside green and red
  • ·Use blue/orange instead of green/red for complementary data — deuteranopes perceive this pair distinctly
  • ·Check your chart colors: if two data lines merge into the same color in the simulation, redesign

Safe color pairs for data visualization:

  • ·Blue (#1A73E8) vs Orange (#FA7B17) — distinct for all color blindness types
  • ·Purple vs Green — distinct for red-green color blindness
  • ·Avoid: Red vs Green, Brown vs Olive, Blue-Green vs Gray

Format comparison

Deuteranopia vs protanopia: Both are red-green color blindness but affect different cone types. Deuteranopia (absent M-cone) makes red and green appear as brownish-yellow. Protanopia (absent L-cone) similarly confuses red and green, but additionally makes red appear very dark — almost black in severe cases. Protanopia has a larger impact on red hues; deuteranopia has a larger impact on green hues.

Deuteranopia vs tritanopia: Tritanopia is blue-yellow color blindness (absent S-cone), affecting about 0.001% of the population — extremely rare. Blue appears green; yellow appears violet or gray. Tritanopia is far less common than red-green types and requires separate design consideration.

Color blindness simulation vs real experience: The simulation approximates the perceptual experience using published mathematical models. Real perception varies between individuals — even people with the same diagnosis experience it differently. Use simulation as a starting point for design decisions, then validate with users who have color vision deficiencies when possible.

How it works

1

Upload or enter color

Drop an image file to simulate how the whole image appears, or enter a single color value to see its deuteranopia equivalent.

2

Apply simulation

A color matrix transformation is applied using the Machado 2009 model, processing colors in linearized RGB space.

3

Compare

View original and simulated side-by-side. Identify color pairs that become indistinct in the simulation.

About this format

Deuteranopia is the most common form of color blindness, affecting approximately 1 in 12 men and 1 in 200 women globally — around 8% of the male population. People with deuteranopia have absent or non-functional M-cones (medium-wavelength cones), which process green light. The result: they cannot distinguish red from green, and instead perceive them both as shades of yellow and brown.

For interface designers, deuteranopia has a direct consequence: any design that uses green to mean "success" and red to mean "error" — without any additional differentiator — will be ambiguous or invisible to 1 in 12 of your male users. Traffic light patterns (green/red status indicators), charts that use red and green as contrasting data series, and form validation that relies on color alone all fail this test.

This simulator applies a color matrix transformation based on the Machado, Oliveira & Fernandes (2009) model, which produces scientifically validated approximations of how colors appear to people with deuteranopia. Upload an image or enter a color to see the simulated view — then use it to make informed decisions about color-based information encoding.

Frequently asked questions

What is deuteranopia?+
Deuteranopia is a form of red-green color blindness caused by the absence of M-cones (medium-wavelength, green-sensitive photoreceptors) in the retina. People with deuteranopia cannot distinguish red from green — both appear as shades of yellow, brown, or olive. It affects approximately 1% of men and 0.1% of women.
What is the difference between deuteranomaly and deuteranopia?+
Deuteranopia is the complete absence of M-cones (dichromatic vision — only two cone types function). Deuteranomaly is a milder form where M-cones exist but have shifted sensitivity (anomalous trichromatic vision). Deuteranomaly is more common (about 5% of men) and less severe — affected individuals can distinguish some red-green differences but have reduced sensitivity.
How do I design interfaces that work for colorblind users?+
Never rely on color alone to convey information. Pair color coding with shape (✓/✗), labels (Success/Error), pattern fills in charts, or border styles. Use the blue-orange pair instead of red-green for data with high contrast requirements. Test every color-coded element using a deuteranopia simulation before shipping.
Which colors are safe to use together for all types of color blindness?+
Blue (#1A73E8) and orange (#FA7B17) is the most widely recommended pair — it remains distinct for deuteranopia, protanopia, and tritanopia. Black and white always work. Blue and red work for red-green colorblindness but may be problematic for tritanopia. Test any critical color pair with a simulation tool for all major conditions.
Does WCAG have accessibility requirements for color blindness?+
WCAG 1.4.1 (Use of Color) requires that color not be the only visual means of conveying information — this applies to all color blindness types. It does not specify which colors are allowed or prohibited, only that color-only differentiation is not sufficient. Pass 1.4.1 by ensuring non-color cues (text, shape, pattern) accompany any color-coded information.
Is this simulation accurate to real deuteranopia?+
The simulation uses the Machado, Oliveira & Fernandes (2009) mathematical model, which is the most widely validated algorithm for color blindness simulation. It provides a close approximation of deuteranopia perception but cannot perfectly replicate individual variation — some people with the same diagnosis perceive colors differently. Use it as a design review tool, not a medical reference.

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