Computational Analysis for Conservation of Works of Art

Scholars in the areas of conservation of art are in need of scientific information that can be reliably used in the historical examination of works of art. Most existing methods for the analysis of the material used in works of art are based on destructive testing techniques that require the physical sampling of data. However, such methods cannot be used widely due to their destructive nature and the historical value of the artifacts. Non-destructive techniques such as reflectography are more suited to the study and conservation of works of art. Computer vision techniques can complement such diagnostic methods by computing models and interpreting the visual properties of the material used. The main objective of this work is the application of machine vision techniques for the non-destructive examination and conservation of works of art based on the modelling and analysis of the colouring present. In this paper we concentrate on the visual modelling of medieval inks used in scripting of manuscripts. Such models can then be used in the analysis and conservation of unknown writing inks found in manuscripts therefore eliminating the use of any destructive techniques.