Abstract
In this paper, we consider the square jigsaw puzzle problem in which one is required to reassemble the complete image from a number of unordered square puzzle pieces. Here we focus on the special case where both location and orientation of each piece are unknown. We propose a new automatic solver for such problem without assuming prior knowledge about the original image or its dimensions. We use an accelerated edge matching based greedy method with combined compatibility measures to provide fast performance while maintaining robust results. Complexity analysis and experimental results reveal that the new solver is fast and efficient.
Highlights
It is generally accepted that the first modern jigsaw puzzle was built in 1760 by London map maker John Spilsbury for educational purposes [1]
The jigsaw puzzle is provably technically challenging. It has been shown by Demaine et al [2] that the jigsaw puzzle problem is NPcomplete in the general case when the pairwise affinity of jigsaw pieces is unreliable
Computational jigsaw assembly is an interesting problem, which plays a vital role in many different scientific fields, such as image processing, computer vision, archeology and genomics
Summary
It is generally accepted that the first modern jigsaw puzzle was built in 1760 by London map maker John Spilsbury for educational purposes [1]. The jigsaw puzzle is provably technically challenging It has been shown by Demaine et al [2] that the jigsaw puzzle problem is NPcomplete in the general case when the pairwise affinity of jigsaw pieces is unreliable. Several papers [11, 12] assume using classic jigsaw pieces with distinct shapes, and focus on matching the shape of the pieces to solve the puzzle. Some others use both of image contents and boundary shape [13, 14, 15]. The rest of the paper is organized as follows: Section II introduces the new jigsaw assembly algorithm.
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