2. Artifacts detection by AI: Quality Check of video files from mass digitization – Denise Barcella | Radio Télévision Suisse | Switzerland
The RTS Quality Check project uses the potential of artificial intelligence (AI), that is to say computer vision, to ease quality control of video files produced by mass digitization. Five algorithms are currently checking almost 400’000 files, resulting from the digitization of 120’000 analogue carriers (mainly Betacam SP), so as to ease human work. Humans have only to examine the results of the algorithms, and, decide if a new digitization is needed.
These 5 algorithms have been calibrated by our project, with the main common anomalies or artefacts that we found in our digitized tv archive collection and categorized according to their type. An interface was also designed to display the results of the algorithms so that humans can make the right decisions easily and efficiently. The main goal was to avoid any loss of our unique audiovisual heritage, because unfortunately, the quality control was not done thoroughly enough during the mass digitization and this for lack of financial and technical means at the time, and because there are threats on the original carriers, like time passing by.
What was a challenge is that RTS Archive Department had to find a solution to carry out this quality control in a context of cost-saving measures and after digitization (which made the process much more complicated). As the potential of AI was raising in almost any field, we decided to try using it in the context of the Quality Control.
