Towards a More Sustainable and Less Invasive Approach for the Investigation of Modern and Contemporary Paintings

Abstract

In Heritage Science, sampling is frequently performed for the subsequent diagnostics of modern and contemporary paintings using invasive analytical techniques. However, it endangers the integrity of artworks, and thus, it should be carefully planned and carried out only as a last resort by specialists. Pigment mixtures have commonly been employed by modern and contemporary artists due to the ease of combining paints on the color palette. Hence, a painting might include both primary/secondary paints and mixtures of those. Therefore, obtaining a sample from a mixture might be sufficient for the identification of the individual primary-colored paints. This study focused on the creation of a user-friendly computational workflow for the analysis of images of paintings for the identification of mixtures using cluster analysis (K-means and Fuzzy C-means clustering). Sixteen modern and contemporary paintings that belong to the International Gallery of Modern Art Ca’ Pesaro in Venice have been selected: seven of them by Guido Cadorin (1892–1976), six by Andreina Rosa (1924–2019), and three by Boris Brollo (b. 1944), and the artworks of the latter being examined for the first time in this study (using Raman and ER–FTIR spectroscopies). It was found that mixtures can be identified in unvarnished paintings that consist of both non-overlapping and vibrant-colored paint layers, like those of Boris Brollo, and overlapping paint layers, like those of Andreina Rosa. Moreover, K-means clustering performs better in the case of non-overlapping colors, whereas Fuzzy C-means in the case of overlapping colors. In contrast, paintings that have been rendered with dark colors and that present a varnish layer, like those of Guido Cadorin, cannot be preliminary investigated in the proposed manner.