The 1000 maximally perceptually-distinct colors

When drawing a graph, we sometimes need to use colors to distinguish different curves. Many years ago, I began to use the Matlab distinguishable_colors function written by Tim Holy to determine the color of the curves used in the paper. However, the output value of distinguishable_colors is not intuitive enough, so I made this page to display the first 1000 color values of distinguishable_colors. And, in order to determine the black and white printing effect of these colors, I calculated the gray values of these colors.

Instruction

The color bricks contain RGB values in uint8 [3] format and in html color format #rrggbb. The grayscale is calculated by Matlab rgb2gray function. The rgb2gray converts RGB values to grayscale values by forming a weighted sum of the R, G, and B components:

G = 0.2989 * R + 0.5870 * G + 0.1140 * B

We can choose the colors that are suitable for both color display and black-white printing according to the gray value. The grayscale value ranges from 0 to 255, a larger grayscale value indicates a lighter printing effect.

Each color brick contains an index value, you are welcome to leave a comment on which index values you prefer to use. 🙂

The 1000 most distinguishable color bricks

Reference

Tim Holy (2020). Generate maximally perceptually-distinct colors (https://www.mathworks.com/matlabcentral/fileexchange/29702-generate-maximally-perceptually-distinct-colors), MATLAB Central File Exchange. Retrieved May 15, 2020.