Archaeological documents or artefacts are usually found in a poor and fragmented state, owing to its long age. They are many times too complex to deal with manually. 

Since the 1960s researchers have been exploring ways to overcome these challenges. There are findings which suggest that in 1964, computational solver was introduced that could solve a nine-piece puzzle. While these were rudimentary efforts, researchers are now using state-of-the-art techniques based on natural images, colour matching, shape matching, and others to design algorithms and solve twisted puzzles in archaeology.

In a recent development, researchers at Technion and University of Haifa, Israel have proposed a new algorithm that is able to fix these issues with computer vision.1

Solving Archaeological Puzzles

Niv Derech, Ayellet Tal, Ilan Shimshoni

(Submitted on 26 Dec 2018)

Puzzle solving is a difficult problem in its own right, even when the pieces are all square and build up a natural image. But what if these ideal conditions do not hold? One such application domain is archaeology, where restoring an artifact from its fragments is highly important. From the point of view of computer vision, archaeological puzzle solving is very challenging, due to three additional difficulties: the fragments are of general shape; they are abraded, especially at the boundaries (where the strongest cues for matching should exist); and the domain of valid transformations between the pieces is continuous. The key contribution of this paper is a fully-automatic and general algorithm that addresses puzzle solving in this intriguing domain. We show that our state-of-the-art approach manages to correctly reassemble dozens of broken artifacts and frescoes.
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:1812.10553 [cs.CV]
  (or arXiv:1812.10553v1 [cs.CV] for this version)