Solving a picture jumble!
algorithm, image
Solution
What you need to do is to define an indexing vocabulary for each face of a jigsaw puzzle, such that the index of a right-facing edge can can tell you what the index of a corresponding left-facing edge is (e.g, a simple vocabulary: "convex" and "concave", with "convex" on a face implying "concave" on a matching opposite face), and then classify each piece according to the indexing vocabulary. The finer the vocabulary, the more discrimantory the face-matching and the faster your algorthm will go, however you implement it. (For instance, you may have "flat edge, straight-edge-leans-left, straight-edge-leans-right, concave, convex, knob, knob-hole, ...). We assume that the indexing scheme abstracts the actual shape of the edge, and that there is a predicate "exactly-fits(piece1,edge1,piece2,edge2)" that is true only if the edges exactly match. We further assume that there is at most one exact match of a piece with a particular edge.
The goal is grow a set of regions, e.g., a set of connected pieces, until it is no longer possible to grow the regions. We first mark all pieces with unique region names, 1 per piece, and all edges as unmatched. Then we enumerate the piece edges in any order. For each enumerated piece P with edge E, use the indexing scheme to select potentially matching piece/edge pairs. Check the exactly-fits predicate; at most one piece Q, with edge F, exactly-matches. Combine the regions for P and Q together to make a large region. Repeat. I think this solves the puzzle.
Problem
What algorithm would you make a computer use, if you want to solve a picture jumble? You can always argue in terms of efficiency of the algorithm, but here I am really looking at what approaches to follow. Thanks