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Collection of image segmentation techniques written
in C and compiled to WebAssembly. Computation time
in parentheses.
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Digital images use gamma encodings to store luminance. Gamma correction can make image luminance appear more realistic.

**K-Means:** A randomized clustering algorithm to
group pixels into K groups based on Euclidean distance
between RGB values. A higher K leads to more detailed
results.

**Mean Shift:** A hill climbing algorithm to
iteratively find local maxima. The kernel size controls
the sensitivity to smaller modes. The least two
significant bits are dropped from each color component.

**Split & Merge:** A two stage algorithm to split an
image into homogenous regions (by subdividing
nonhomogeneous blocks into quadrants) and then merge
similar neighboring blocks into groups. The tolerance
controls the threshold at which blocks are deemed
homogenous.

**Balanced Histogram Thresholding:** An automatic
thresholding method that divides the color space by
finding the midpoint of an RGB histogram.