Ishihara's Tests for Colour Deficiency
Authentic and accurate images of Ishihara's test plates
Just because it's black in the dark,
Oh, doesn't mean there's no colors.
— Laleh (Colors)
Authentic and color-accurate images of Ishihara's test plates for colour deficiency.
I provide high-resolution bitmaps and SVG files for each plate. I also provide the position, size, and color of each circle on each test plate.
Can this information be used to make fakes? Yes, but at least they'll be really good ones. Also, please don't.
If you're interested to learn more about colorblindess and the mathematics behind it, see my Designing for Color Blindness, Palettes for Color Blindness and Math of Color Blindness.
And turn those lines of confusion into understanding!
contents
Authentic and color-corrected images of Ishihara's test plates for color deficiency. These were photographed (methods) from the 38 plate book.
The plates are 12 × 12 cm. The circular pattern of dots on each plate is approximately 9 cm in diameter.
Image archives include all the plates and images of the Gretag-Macbeth colorchecker at various stages of color correction.
400 × 400 pixels (84 dpi).
400 × 400 pixels (84 dpi), 2,419 × 2,419 pixels (512 dpi), and SVG.
The SVG files contain links to the hires images.
You didn't just come here for the images. You want to know the position, size, and color of each circle on each test plate.
There are 25,090 circles across all 38 plates. The number of circles on each plate is: 1 (588), 2 (735), 3 (676), 4 (655), 5 (672), 6 (744), 7 (660), 8 (782), 9 (721), 10 (758), 11 (724), 12 (542), 13 (579), 14 (771), 15 (723), 16 (593), 17 (586), 18 (735), 19 (594), 20 (607), 21 (570), 22 (734), 23 (714), 24 (636), 25 (603), 26 (661), 27 (650), 28 (667), 29 (688), 30 (720), 31 (592), 32 (725), 33 (581), 34 (623), 35 (638), 36 (648), 37 (616), and 38 (579).
This file contains the position, radius, and RGB color of these circles, sorted by plate (ascending), radius (descending), x position (ascending). The circles were identified with this code, applied to my high-resolution color-corrected photographs of each plate. The RGB color in the SVG file is the average RGB value across pixels in each circle.
The units are arbitrary. Each SVG canvas is 2,419 × 2,419 pixels and corresponds to 12 × 12 cm.
# plate x y radius R G B 1 1313 835 53 253.06855718292303 138.0174509192895 82.55936428794017 1 1554 1543 53 254.0174509192895 134.86631349330008 80.13804923652228 1 1558 1172 53 253.7310688688065 135.0819569959489 80.92489872234341 1 1659 753 53 253.2848239326893 135.6849485821128 81.9164848862574 1 1667 1507 53 253.87815518853225 134.71019009037082 80.34340916173262 1 1722 904 53 253.27454035525085 136.30850732315363 81.9460891243378 ...
Happy 2026 π Day—
Art for the 5%
Celebrate π Day (March 14th) and enjoy the art — but only if you're part of the 5%.
Go ahead, see what you can't see.
Ishihara's Tests for Colour Deficiency
Authentic and accurate images of Ishihara's test plates photographed (and lovingly color-corrected) from the 38-plate Ishihara's Tests for Colour Deficiency.
I also provide the position, size, and color of each circle on each test plate.
Symmetric alternatives to the ordinary least squares regression
What immortal hand or eye, could frame thy fearful symmetry? — William Blake, "The Tyger"
This month, we look at symmetric regression, which, unlike simple linear regression, it is reversible — remaining unaltered when the variables are swapped.
Simple linear regression can summarize the linear relationship between two variables `X` and `Y` — for example, when `Y` is considered the response (dependent) and `X` the predictor (independent) variable.
However, there are times when we are not interested (or able) to distinguish between dependent and independent variables — either because they have the same importance or the same role. This is where symmetric regression can help.
Luca Greco, George Luta, Martin Krzywinski & Naomi Altman (2025) Points of significance: Symmetric alternatives to the ordinary least squares regression. Nat. Methods 22:1610–1612.
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Kurz, C.F., Krzywinski, M. & Altman, N. (2025) Points of significance: Propensity score weighting. Nat. Methods 22:638–640.