When the frescoed ceiling of Assisi’s Basilica of St. Francis crashed to the floor two-and-a-half years ago, few people would have imagined the resulting fragments of painted plaster would present information technology with one of its most intriguing challenges.
The earthquake of Sept. 26, 1997, killed four people in the church and transformed priceless paintings by Giotto and Cimabue into a heap of dust and coloured rubble. Since then, restorers have been painstakingly piecing together the fragments and have enlisted the help of computers to tackle their most difficult task: the reassembly of Cimabue’s 13th century portrait of St. Mathew.
The triangular 32 square-metre painting, which shows the evangelist reading at a desk, was shattered when it fell 22 metres to the floor. “The painting was so badly damaged that its reassembly would probably be impossible without the assistance of computer technology,” says Professor Giovanni Iacovitti, who is coordinating the IT effort. Iacovitti, head of the Information and Communication Department at Rome’s La Sapienza University, leads a team of IT experts from the university and art restorers from the Central Institute of Restoration (ICR).
Initial results are encouraging. The team began by creating a copy of part of the fresco, measuring 40 by 40 centimetres, and breaking it into fragments similar in size to those of the original. Cimabue’s work is currently broken into about 120,000 fragments with an average diameter of 2 centimetres. Laid out in trays on a black foam base, the pieces were digitally scanned by a 6,000-by-7,000 pixel camera.
Using C++ and Mathlab software on Pentium workstations, the team developed its own software for the isolation and acquisition of the fragments and went on to develop a program that matches the pieces with the corresponding parts of a photographic reproduction of the original. “We decided to develop algorithms of our own because we found the commercially available programs to be unsatisfactory,” Iacovitti says. “They were unable to cope with ambiguity, for example, where an area of black from the fresco met the black foam of the background.”
The programs must adjust the scale to that of the available photographs and harmonize the colours of the photos with the results of the digital scanning. They also have to compensate for geometric distortion, since the original work was attached to the curved surface of the basilica’s vault. Finally, they match the fragment images with their equivalent in the unfragmented fresco — each examined fragment rotating constantly until it finds its location in the original.
Iacovitti’s program provides likelihood maps, often suggesting a single match, sometimes offering a range of choices listed in order of probability. The computer cannot compete with the visual recognition capabilities of humans, but it performs a repetitive task accurately and fast.
Restorers will begin applying the technique to the original fragments this spring and hope to finish by the end of the year. Digital scanning was completed last March, with around 900 trays of fragments creating a 150GB database and filling 130 CDs. Each fragment is individually memorized and has its contours highlighted, while its individual code tells restorers where to find it.