Improved anti-aliasing

Nobody has claimed this yet.

We've seen quite a few false positives that are due to the anti-aliasing algorithm not *quite* getting it right when the shape being anti-aliased is quite thin or forms a ring.

The issue comes from the algorithm's reliance on both the darkest and lightest neighbour being "definitely not antialiased" -- which is detected via having at least 3 neighbours of equal color. However, in such cases above, one of the two will not be. Here's an example:

In the image above the orange arrow points at the candidate anti-aliased pixel, and the purple arrow at the darkest neighbour. Notice that because the shape drawn (a dark grey circle in this case) is quite thin (1px wide) we don't end up finding 3 other pixels in the neighbourhood of the dark grey pixel of equal color.

I think an idea to improve the algorithm would be to perhaps relax the constraint on *one* of the darkest or lightest (with the assumption that the other is a region of flat color and should have plenty of neighbours). Perhaps the relaxed condition could be simply that it has some neighbours of relatively close color? I'm not quite sure. I want to put together a few test cases.

In any case I was interested in your thoughts. Have you thought about this problem before?

Start by reviewing the anti-aliasing algorithm and how it identifies darkest and lightest neighbours. Use the thin-shape and ring cases described in the issue to define test cases, then determine and validate a less restrictive condition for one neighbour. Done means the relevant false positives are addressed without regressing existing image comparisons.

Written by the indexing model from the issue text.