Abstract
The philosophical and theoretical foundations of the Theory of Restoration, envisioned by Cesare Brandi in 1975, are established around clear and straightforward guidelines on what is ethically acceptable, and unacceptable, in conservation. Specifically, the Italian scholar advocates for the complete reversibility of restoration work and respect for the history of an artwork. Indeed, according to these concepts, all interventions should be fully reversible so to return the object to its initial conditions without any damage. Bearing in mind these assumptions, a detailed documentation of all the steps of the conservation process, and the possibility to retrieve them a posteriori, must be considered essential. This concept especially applies when dealing with paintings restoration characterized by fine and small details. In recent years, the tendency is to favour minimal invasive interventions ranging from consolidation actions, cleaning samples, and colours retouching. Materials change more or less conspicuously over time according to their consistency and the intensity of the changing factors. Icons do not make an exception to this rule. This process affects the icon’s whole structure: the support, the painting itself and the varnish coating. This paper investigates the performance of change detection algorithms, developed in the remote sensing domain, and, in the framework of this research applied at a microscale (paintings). Each phase of the restoration process is documented exploiting a multi-epoch image acquisition. A monitoring methodology coupled with photogrammetry and 3D shape analysis is tested and described. It is anticipated that the proposed innovative use of change detection techniques can be applied to different kinds of painted surfaces. An icon, today preserved at the Byzantine Museum Makarios III Foundation in Nicosia and restored by the Department of Antiquities of Cyprus labs, has been used as a case study.
Highlights
For almost the last two decades digital technologies have been increasingly used to address art conservation problems and provide objective diagnostic and documentation tools.Concerning the restoration of paintings, the scientific community has proposed a variety of methodologies for the study, identification, and mapping of the decay
As mentioned in “2D change detection” section, the lowest order Multivariate Alteration Detection (MAD)-Maximum Autocorrelation Factor (MAF) component is initially used to detect the changes that occurred on the icon surface
Time 0: initial conservation status of the painting Before the beginning of the restoration process, the conservation status of the icon was assessed through visual analysis
Summary
Concerning the restoration of paintings, the scientific community has proposed a variety of methodologies for the study, identification, and mapping of the decay. Techniques such as multispectral analysis [1], virtual restoration [2], Geographical Information System (GIS) [3], and 3D modelling [4] have proven to be successful when integrated in a multidisciplinary research environment. The documentation process of painted artworks is today mainly realised through digital cameras using direct or oblique light, coupled, when possible, with colour checkerboards and metric rulers. The collected images are a posteriori visually analysed to identify the changes the artworks went through during the restoration. The proposed study presents a novel way to exploit change detection procedures
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