Scanned Vertical Artwork Cloud
Dr David Selviah, Reader in Optical Devices, Interconnects, Algorithms and Systems in UCL Electronic and Electrical Engineering, has completed work on Technology Strategy Board (TSB) Smart award funded project “Scanned Vertical Artwork Cloud (SVAC)”. UCL carried out the research in partnership with Worknet Ltd (www.worknet.co.uk) , a UK hosted desktop and IT services SME company, as part of a £100k project running over 9 months and ending in August 2013. The Technology Strategy Board is jointly funded by the UK Government Department for Business, Innovation and Skills (BIS) and other UK government departments, devolved administrations, regional development agencies and research councils
UCL brought its algorithmic programming, motion control and optical design expertise and Worknet brought its remote server environment and hosting expertise to the successor to an earlier TSB funded FastTrack “Digital Art Capture (DAC)” project, in which UCL demonstrated the feasibility of constructing a 2D scanning microscope to capture overlapping ultra-high resolution photographs of artwork laid in the horizontal plane facing upwards. That system was trialled by Tate Gallery who gave a very favourable review and identified a number of possible improvements and additional functionality, which would increase the flexibility of the system. In this project, the system was tested over a larger area and upgraded to be capable of scanning vertically mounted artwork. This was deemed vitally important by Tate Gallery as it is neither desirable nor convenient to move fragile and valuable artwork unnecessarily. The original novel software was further developed by UCL to run on a distributed ("Cloud") platform rather than a local laptop computer and the functional area increased to A4, requiring the recording, transmission and manipulation of data files of 350 Gb in total. The aim of this project was to prove the concept of a vertical scanning mechanism, and the portability of the software onto a hosted platform.
Dr Selviah and Dr Hadi Baghsiahi successfully demonstrated the robotic recording system by recording a variety of forms of artwork both flat and those having a slightly raised surface texture. The recording system was designed to be able to deal with severely warped artwork canvases. Worknet showed that the application of a distributed processing platform held significant advantages over stand-alone machines and that image alignment and manipulation times were reduced.