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The function domCol below is about 100 times faster than DominantColors. Basic plan: Create enough color bins throughout the color space occupied by the image; count the number of pixels in each bin; return the sorted colors. The function works in the LAB color space so we can use EuclideanDistance for the distance between colors. The centers of the bins ...


Use of ColorQuantize Much faster. Not exactly the same, but close and for an art project is OK I think. i = ExampleData[{"TestImage", "Lena"}]; QuaCol[i_, n_] := RGBColor /@ Union[Flatten[ImageData[ColorQuantize[i, n]], 1]]


The problem is not with DominantColors Try varying the number of colours selected by running this snippet. I vary the number of selected colours from 1 to 10, and measure the time to calculate DominantColours ten times: Table[ First@AbsoluteTiming@ Table[DominantColors[p, i], {p, RandomChoice[pieces, 10]}] , {i, 10}] (* {6.544491, 7.658153, ...

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