Merging of Coplanar and Adjacent Polygons - Leith's Algorithm

I wanted to find the Union of a set of coplanar polygons, so initially, I tried to 'weld' the polygons together based on an exhaustive search for 'shared edges',  however in my 'simple test case', I am dealing with hundreds of simple polygons at a time, and missing a special case or two made debugging absolute hell.
Despite the algorithm showing promise, its performance was bound to degrade as the polygon count increase - and 'logarithmically-so'.
I had to find a better solution, abandoning this solution pathway even though I had racked up several days trying to make it work.

The (much faster, and better-scaling) alternative I am trying right now is very similar to a half-edge implementation - I feed all the edges of all coplanar polygons into a map of Directed Edges, and then having done so, I search the map for a reversed case of each input edge - if two polygons refer to the same edge, but with reversed order of vertices, then that edge is NOT a boundary edge, its an internal feature of the bounded shape, and therefore not interesting. If we fail to find a matching reversed-edge for any given input edge, then that edge must be a Boundary Edge, a part of the bounds of the (possibly convex) bounded shape. In this case, I'll collect the edge, and at the end of this process, I'll have a bunch of edges which are directed edges on the boundary of the shape - if the shape is non-manifold, I'll be able to discover each 'island' exactly the same way.

SourceCode is written, time to test the theory.