Isthmus critical points for solving jigsaw puzzles in computer vision

A computer vision system that can assemble canonical jigsaw puzzles is described. The most novel aspect of this system is that the methodology derives a new set of critical points that define a feature that can be used in matching partial boundaries (or contours) of planar regions. This global feature, called an isthmus, can be efficiently and reliably computed from the Euclidean skeleton or medial axis transformation of an object. A heuristic matching technique using isthmus critical points is applied to the partial boundary matching problem of jigsaw puzzle fitting. The isthmus may also be a useful feature in any application in which the point of narrowest necking of a planar region needs to be located