Solving Multiple Square Jigsaw Puzzles With Missing Pieces

Genady Paikin, Ayellet Tal; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 4832-4839

Jigsaw-puzzle solving is necessary in many applications, including biology, archaeology, and every-day life. In this paper we consider the square jigsaw puzzle problem, where the goal is to reconstruct the image from a set of non-overlapping, unordered, square puzzle parts. Our key contribution is a fast, fully-automatic, and general solver, which assumes no prior knowledge about the original image. It is general in the sense that it can handle puzzles of unknown size, with pieces of unknown orientation, and even puzzles with missing pieces. Moreover, it can handle all the above, given pieces from multiple puzzles. Through an extensive evaluation we show that our approach outperforms state-of-the-art methods on commonly-used datasets.