Shattered remains of once majestic works of art can now be digitally recreated and restored to their former glory thanks to a team of archaeologists.
Researchers have built an AI-powered algorithm that predicts what should surround a surviving archaeological fragment and locates its neighbouring piece.
A virtual image is then produced which aids in the meticulous physical reconstruction of the item.
Archaeologists at Technion and the University of Haifa in Israel say this programme could save endless hours in the restoration of historical items.
Trials with the technology were conducted on pieces of ancient statues and Byzantine frescoes from Cyprus.
‘Puzzle solving has been an intriguing problem for many years,’ the researchers write in their paper, pre-published on arXiv.
‘It has numerous application areas, such as in shredded documents, image editing, biology and archaeology.’
Fragile remnants of the past often resurface in scattered pieces and full restoration is a time consuming and arduous process.
‘Archaeological artefacts are not “clean” and “nicely behaved”; rather they are broken, eroded, noisy and ultimately extremely challenging to algorithms that analyse or reassemble them,’ the researchers say in their paper.
Three major issues archaeologists face when working to rebuild artefacts are abrasion, colour fading and continuity.
Abrasion creates gaps between pieces and makes neighbouring pieces hard to find.
Colour fading makes distinguishing between real and false edges hard to decipher and the irregular nature of the fragments gives an almost infinite amount of possibilities.
Mike Heyworth, director of the Council for British Archaeology, told The Times: ‘In the analysis of excavated material it is often time-consuming and laborious to match fragments of artefacts such as ceramic vessels which go together and can help to add to our understanding of the finds and their context.’
The algorithm created by the academics used creases in the clothing of figures to project what the next pieces should look like.