[rjkaplan]

Author here. That's a neat trick!

> I mention this because the mystery of the getDistance() function is often one of the tricky parts of demos like these.

I agree! In the demos I use a library I wrote to generate 2D distance fields: https://github.com/ryankaplan/gpu-distance-field

It's also pretty fast :)

[johndough]

Computing distance fields with a jump flooding approach in O(n log n) is neat, but there is a O(n) algorithm, which might be faster https://prideout.net/blog/distance_fields/

[rjkaplan]

Neat! In my experience jump flooding on the GPU is faster than any CPU side approach for images bigger than a few hundred pixels. It's O(n ^ 2 log n) which sounds really expensive, but it requires just O(log n) draw calls.

The link you provided also describes a GPU amenable approach, but it says that jump flooding on the GPU is faster.

> For a more efficient GPU-amenable method, see also jump flooding by Rong and Tan. Their method generates a closest point coordinate field from which a distance field can be derived.