Summary
This paper describes LADDER, a cool language developed for describing shapes for
recognition purposes. Using LADDER, one can define shapes by describing geometric constrains between primitives, lines, curves, arcs, rectangles, polygons etc. These constraints define how these primitives should interact with each other to form a meaningful shape. The constraints are based on human perception rather than precise distance measures, such as parallel, above, perpendicular etc.
Using LADDER, it is also possible to construct high level shapes using low level constructed shapes. So it works like nesting matryoshka dolls in that sense. It is also possible to specify options to override recognition and allow beautification.
Discussion
LADDER is a first. I think it is pretty cool in that sense. I really like that it uses relaxed constraints based on human cognition rather than scientific measure. Some challenge to it is that it becomes harder to define shapes programmaticly as complexity and details increases. However, it sill works fine most of the time.
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