Color Blindness Simulator

See your image through the eyes of someone with a color vision deficiency. Choose the type, preview and download the result. Everything runs in your browser.

How Color blindness simulator works

Color Blindness Simulator applies colour-transformation matrices to your image to show how it appears to people with protanopia (red-blind), deuteranopia (green-blind), tritanopia (blue-blind) or achromatopsia (complete colour blindness). The matrices are applied pixel by pixel using Canvas.getImageData() and Canvas.putImageData() in your browser. No image data is transmitted to a server.

The simulations are based on published perceptual models derived from studies of colour vision deficiency. They are approximations of how the visual system of an affected person processes colour, not exact reproductions of individual experience, which varies. The tool is designed to help designers and developers identify contrast or colour-coding problems that would affect a significant share of their audience: around 8 percent of men and 0.5 percent of women have some form of colour vision deficiency.

Written by Bastien Sulyan

How to use Color blindness simulator, step by step

Drop your image onto the upload area or click to browse.
Select a colour vision deficiency type from the menu: protanopia, deuteranopia, tritanopia or achromatopsia.
View the simulated result alongside the original in the comparison panel.
Toggle between simulation types to compare how each condition affects the image.
Use the side-by-side view to identify areas where colour alone conveys information that may be lost.

Common use cases

A UI designer checks whether a red-green status indicator is distinguishable for users with deuteranopia before shipping a feature.
A data visualisation author verifies that a multi-line chart with colour-coded series remains readable in the protanopia simulation.
A brand designer evaluates how a logo with gradient colours reads under achromatopsia to ensure it retains recognisable shape and contrast.
A game developer tests whether colour-coded map zones are distinguishable for players with tritanopia and adds pattern fills to supplement colour coding.

Frequently asked questions

How accurate are the colour blindness simulations?

The simulations apply perceptual transformation matrices derived from published research on colour vision deficiency. They are scientifically grounded approximations of typical cases of each condition. Individual experience varies: severity differs between people with the same diagnosis, and the simulation cannot account for compensatory strategies that some users develop. Treat the output as a useful indicator, not a definitive test.

Does the tool cover all types of colour blindness?

The four types covered are the most common forms of colour vision deficiency and complete colour blindness. Anomalous trichromacy types (protanomaly, deuteranomaly, tritanomaly), which represent partial deficiencies, are not separately modelled in the current version.

Is my image analysed on a server to produce the simulation?

No. The colour matrix transformation is computed locally using Canvas.getImageData() to read the pixel array and Canvas.putImageData() to write the result. All processing happens inside the browser tab and the image data stays on your device.

Can I use this tool to check colour contrast ratios?

This tool shows how colours appear to people with colour vision deficiency but does not calculate WCAG contrast ratios numerically. For numerical contrast checking, use the Color Converter tool, which includes a WCAG contrast checker.

Does the tool work with images that contain text?

Yes. The transformation is applied to the entire pixel array, including any text rendered in the image. This lets you check whether text colour against its background remains legible under each simulated condition.

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