Color Blindness Simulator
Upload any image and simulate how it appears to people with different types of color vision deficiency. All processing happens in your browser.
Protanopia Simulation
About Color Blindness Simulation
Color blindness, or color vision deficiency (CVD), affects approximately 300 million people worldwide. About 8% of men and 0.5% of women of Northern European descent have some form of color vision deficiency. This simulator helps designers, developers, and content creators understand how their visual content appears to people with different types of CVD, enabling them to create more inclusive and accessible designs.
The most common types of color blindness involve the red-green spectrum. Deuteranomaly, a reduced sensitivity to green light, is by far the most prevalent form, affecting roughly 5% of all males. Protanomaly (reduced red sensitivity) and protanopia (complete absence of red cone cells) each affect about 1% of males. Deuteranopia, the complete absence of green cone cells, also affects approximately 1% of males. These red-green deficiencies make it difficult to distinguish between reds, greens, browns, and oranges.
Blue-Yellow and Total Color Blindness
Less common but equally important are blue-yellow deficiencies. Tritanopia and tritanomaly affect blue-yellow perception and are extremely rare, occurring in fewer than 1 in 10,000 people regardless of sex. Achromatopsia, or total color blindness, is the rarest form where a person sees only in shades of gray. The partial variant, achromatomaly, produces severely washed-out color perception. Understanding these conditions is critical for ensuring that color is never the sole method of conveying information in your designs.
Web Accessibility and WCAG Guidelines
The Web Content Accessibility Guidelines (WCAG) 2.1 specifically address color usage in Success Criterion 1.4.1: "Color is not used as the only visual means of conveying information, indicating an action, prompting a response, or distinguishing a visual element." This means interactive elements should use shape, text labels, or patterns in addition to color. WCAG also mandates minimum contrast ratios (4.5:1 for normal text, 3:1 for large text) under Success Criterion 1.4.3. This simulator uses well-established color transformation matrices derived from research by Brettel, Vienot, and Mollon to produce accurate representations of each vision type. By testing your images and UI designs through this tool, you can identify potential accessibility barriers before they reach users.
FAQ
Q: How accurate is this color blindness simulation?
A: This simulator uses scientifically established color transformation matrices based on the Brettel-Vienot-Mollon model. These matrices transform RGB values through LMS (Long, Medium, Short cone response) color space to simulate the effect of missing or reduced cone cell function. While no simulation can perfectly replicate subjective visual experience, these algorithms are widely used in accessibility research and testing tools, and are considered the standard approach for CVD simulation.
Q: Which type of color blindness should I test for?
A: At minimum, test for deuteranopia and protanopia, as red-green deficiencies collectively affect about 8% of males. For thorough coverage, also check tritanopia (blue-yellow) and achromatopsia (total). If your content passes all four severe types, it will also work for the milder anomaly variants. Deuteranomaly alone covers the single largest affected group.
Q: How can I make my designs more accessible to color-blind users?
A: Use high-contrast color combinations that remain distinguishable across CVD types. Add icons, patterns, text labels, or underlines alongside color cues. Avoid relying on red-green distinctions for critical information like error vs. success states. Use tools like this simulator to verify your palette, and consider providing a high-contrast or color-blind-friendly theme option.
Q: Is my image data safe when using this tool?
A: Yes. This tool runs entirely in your browser using the HTML5 Canvas API. Your images are never uploaded to any server. All pixel manipulation happens locally on your device, and the image data stays in your browser's memory only while you use the tool.