An Adaptive Colour Calibration for Crowdsourced Images in Heritage Preservation Science

In this paper, an adaptive image calibration technique suitable for cultural heritage surveillance in controlled environments is proposed. Heritage pieces, as objects important to conserve, are prone to degradation and thus in the need of a constant watch in order to assess the moment where maintenance is required, preferably in a non-invasive way. By means of a crowdsourcing approach, we take as surveillance cues the pictures visitors take of the piece under surveillance to avoid the need of a permanent human effort on monitoring. In this paper we propose a novel image calibration approach destined to monitor the state of a cultural heritage piece taking as information cues photographs of different sources. Our technique aims to surpass the colorimetry difference between pictures taken by different cameras, performing an adaptive linear interpolation having a given display with a set of colours as reference values, thus transforming the initial colour space of any picture to a fixed one. This is performed in the RGB domain. Lastly, the pictures are transformed to the CIELAB space to extract the colour coordinates and measure the overall objective quality of the calibration. Acting like this allows the heritage monitoring of its possible degradation along time in an effective way without incurring in expensive resources.