How a color looks with protanopia, deuteranopia or tritanopia (red, green or blue color blindness), using the Machado et al. (2009) model.
Actualizado Ejemplos verificados: 4
Without green-sensitive (M) cones, #E74C3C is seen roughly as #9F8F36, a shift of 0.188 in OKLab distance. Don't rely on this hue alone to carry meaning; pair it with text, shape or a lightness difference.
Machado et al. severity-1.0 matrix, applied in linear RGB as colorspacious and DaltonLens do.
Channels are clipped to 0–1 before the sRGB curve and rounded half up to 8 bits.
The simulator converts the color from sRGB to linear light, multiplies it by the Machado, Oliveira and Fernandes (2009) matrix for the chosen type of color vision deficiency, clips each channel to the 0–1 range and converts back to sRGB. The severity 1.0 matrices used here model complete loss of the red-sensitive (protanopia), green-sensitive (deuteranopia) or blue-sensitive (tritanopia) cones. The color shift is the straight-line distance between the original and simulated colors in OKLab.
Designers use it to check whether a color still carries its meaning for people with color vision deficiency. The default red, #E74C3C, becomes the olive #9F8F36 with deuteranopia, a shift of 0.188 in OKLab, and #786D39 with protanopia.
The milder anomalous forms, such as deuteranomaly, are more common than the complete ones and shift colors less, so the simulation shows the strongest effect. Displays and viewing conditions also change how colors look.
Fuente de comprobación: Separate Python 3.8 decimal script: sRGB → linear (IEC 61966-2-1), Machado 2009 severity-1.0 matrix, clamp, re-encode, round half up
Fuente de comprobación: Separate Python 3.8 decimal script: first matrix column (0.152286, 0.114503, −0.003882) re-encoded; blue clamps to 0
Fuente de comprobación: Each Machado matrix row sums to 1 within 1e-6, so linear (1, 1, 1) maps to itself (Python 3.8 row sums)
Fuente de comprobación: Separate Python 3.8 decimal script: third matrix column (−0.178779, 0.147602, 0.303900) re-encoded; red clamps to 0
About 8% of men and 0.4% of women of European ancestry have red-green color deficiency, according to a 2012 review of population surveys by J. Birch in the Journal of the Optical Society of America A; among men of Chinese and Japanese ethnicity the figure is 4% to 6.5%. The US National Eye Institute puts it at about 1 in 12 men.
Each is the complete loss of one type of cone. Protanopia (no red-sensitive cones) and deuteranopia (no green-sensitive cones) make red and green impossible to tell apart. Tritanopia (no blue-sensitive cones) confuses blue with green, purple with red and yellow with pink, according to the US National Eye Institute. The milder forms, protanomaly, deuteranomaly and tritanomaly, shift colors less.
Deuteranomaly, reduced sensitivity of the green-sensitive cones that makes some greens look redder, is the most common type, according to the US National Eye Institute. Red-green deficiencies as a group are far more common than blue-yellow ones. This simulator shows deuteranopia, the complete form of the same deficiency, which is the strongest case of that confusion.
Don't use color as the only way to convey information. WCAG 2.2 success criterion 1.4.1, Use of Color (level A), requires another visual cue such as text, a pattern or an icon, and criterion 1.4.11, Non-text Contrast (level AA), asks for a 3:1 contrast ratio between interface components or graphics and the colors next to them. Check important color pairs here under all three types.
La precisión depende de tus datos y de los supuestos del método. El cálculo decimal usa 50 cifras significativas, pero las estimaciones, los métodos numéricos y los datos de origen pueden ser menos precisos; el redondeo mostrado no elimina esos límites. Ejemplos resueltos comprobados con fuentes independientes: 4. Por ejemplo, «Alizarin red with deuteranopia» se comprueba con Separate Python 3.8 decimal script: sRGB → linear (IEC 61966-2-1), Machado 2009 severity-1.0 matrix, clamp, re-encode, round half up.
Machado, Oliveira & Fernandes (2009), A Physiologically-based Model for Simulation of Color Vision Deficiency, IEEE TVCG 15(6):1291–1298; Machado et al. — simulation matrices for severities 0.1 to 1.0; DaltonLens — Understanding CVD simulation (matrices apply to linear RGB).
Esta calculadora incluye 4 ejemplos resueltos con respuestas de fuentes independientes. Forman parte del conjunto de pruebas y también puedes ejecutarlos aquí.
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