In this paper we propose the first effective automated, genetic algorithm(GA)-based jigsaw puzzle solver. We introduce a novel procedure of merging two"parent" solutions to an improved "child" solution by detecting, extracting,and combining correctly assembled puzzle segments. The solver proposed exhibitsstate-of-the-art performance solving previously attempted puzzles faster andfar more accurately, and also puzzles of size never before attempted. Othercontributions include the creation of a benchmark of large images, previouslyunavailable. We share the data sets and all of our results for future testingand comparative evaluation of jigsaw puzzle solvers.
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