Sequence Matching Genetic Algorithm for Square Jigsaw Puzzles

Abstract : Our paper presents a new method for solving the rectangle piece jigsaw puzzle problem. The puzzle image is RGB full color and because of uniform shape of the individual pieces the process of puzzle assembly is based on information of the pixel values along the border line of the piece only. We have utilized a genetic algorithm that searches for the optimal piece arrangement using dissimilarity between adjacent pieces as the measure of progress. Unlike the previous attempts to utilize genetic algorithms to solve the problem, we have proposed a new heuristic asexual operator that aims at identification of points of fraction within partially assembled picture, extraction of supposed sequence of correctly joint pieces, and its insertion into a new position in such a way that, if possible, the segment is enlarged. Our approach has been successfully tested and the algorithm is capable of solving puzzles consisting of several hundred pieces.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.317-324, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_31〉
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Josef Hynek. Sequence Matching Genetic Algorithm for Square Jigsaw Puzzles. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.317-324, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_31〉. 〈hal-01391329〉

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