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I suspect calculating the average RGB of each emoji and comparing the distances between the average RGB of subsections of the image would have resulted in bette

I suspect calculating the average RGB of each emoji and comparing the distances between the average RGB of subsections of the image would have resulted in better emoji choices and better output (simpler, too). I mean, I get that maybe it’s not the point of this article, but I think the end result would have been a better ‘mosaic’.

thfuran 4y ago
Rgb isn't a great color space to use with distance measures. CIELAB is better, though really perceptually uniform color difference measures are still nontrivial in that space as well.
williamcotton 4y ago
Take a look at the ‘12’ on the bottle of scotch. Higher resolutions than the dimensions of the emoji pixels would otherwise warrant are achieved by selecting emoji that work akin to subpixel antialiasing.
- Llamamoe 4y ago
  I'd reckon there's probably room for about 2x2 subpixels' worth of "antialiasing", making the search space 4x3=12 dimensional (probably in Lab colorspace). Is that doable? If yes I'd expect the approach to be close to optimal possible.
auraham 4y ago
I think there is an algorithm for determining the dominant color in an image (in this case, in a emoji). I do not its name, though. https://stackoverflow.com/questions/3241929/python-find-dominant-most-common-color-in-an-image https://stackoverflow.com/questions/3241929/python-find-domi... https://dev.to/producthackers/creating-a-color-palette-with-javascript-44ip https://dev.to/producthackers/creating-a-color-palette-with-...