Researchers from the University of Oxford and the University of Southampton have developed a Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts (funded by the UK Arts and Humanities Research Council and the Andrew W. Mellon Foundation) to capture images of some of the world's most important historical documents. Recently this system was used on objects held in the vaults of the Louvre Museum in Paris.
These images have now been made available online for free public access on the Cuneiform Digital Library Initiative website.
Among the documents are manuscripts written in the so-called proto-Elamite writing system used in ancient Iran from 3,200 to 3,000 BC and which is the oldest undeciphered writing system currently known. By viewing extremely high quality images of these documents, and by sharing them with a community of scholars worldwide, the Oxford University team hope to crack the code once and for all.
Dr Jacob Dahl, a co-leader of the Cuneiform Digital Library Initiative and a member of Oxford University's Faculty of Oriental Studies, said: 'I have spent the last ten years trying to decipher the proto-Elamite writing system and, with this new technology, I think we are finally on the point of making a breakthrough.
'The quality of the images captured is incredible. And it is important to remember that you cannot decipher a writing system without having reliable images because you will, for example, overlook differences barely visible to the naked eye which may have meaning. Consider for example not being able to distinguish the letter i from the letter t.'
The reflectance transformation imaging technology system designed by staff in the Archaeological Computing Research Group and Electronics and Computer Science at the University of Southampton comprises a dome with 76 lights and a camera positioned at the top of the dome. The manuscript is placed in the centre of the dome, whereafter 76 photos are taken each with one of the 76 lights individually lit. In post-processing the 76 images are joined so that the researcher can move the light across the surface of the digital image and use the difference between light and shadow to highlight never-before-seen details.