How I Built a Perceptual Color Quantization Engine for LEGO Mosaics

The Problem Converting a photo into a LEGO mosaic sounds simple: resize the image, find the closest LEGO color for each pixel, done. Except it looks terrible. Skin tones turn green. Hair becomes a muddy blob. The algorithm picks colors that are mathematically close in RGB but perceptually wrong. The Solution: OKLab Color Space I switched from RGB to OKLab, a perceptually uniform color space designed in 2020. In OKLab, equal numerical distances correspond to equal perceived color differences. This alone was a massive improvement, but it wasn't enough. Material-Aware Matching LEGO bricks aren't paint. A matte red brick and a transparent red brick look completely different under the same light. My engine models each brick's material properties (matte, transparent, metallic, glitter) and weights the color distance accordingly. // Simplified: material-aware distance function colorDistance(pixel, brick) { const labDist = oklabDistance(pixel, brick.co