Frequently, the study of modern and contemporary paintings requires the taking of micro-samples to gain an in-depth understanding of the employed materials and techniques. However, since this procedure is characterized by its invasive nature, it must be carried out only if strictly necessary. This study aimed to evaluate the potentiality of K-means clustering to the corrected images of paintings to identify mixtures of pigments. This could assist in obtaining relevant preliminary information, facilitate the research process, and guide the sampling collection. Additionally, this method would be less expensive than the traditional multi-analytical approach as it would only require a modified digital camera, lenses, a color target and three computational resources for the processing of data (Imatest Master, Adobe Express—online, and R), out of which the latter two are freely available. The six paintings that have been selected for this study belong to the International Gallery of Modern Art Ca’ Pesaro in Venice (Italy) and have been depicted by Andreina Rosa (1924–2019), a Venetian artist. The artworks were thoroughly investigated mainly through non-invasive analytical techniques (FORS, RAMAN, ER-FTIR, EDXRF). Using cluster analysis, simulating mixtures, and calculating the color differences, it was possible to infer the existence of color mixtures of two/three detected primary colors from the examined images, which could be validated by the analytical results. Hence, it was concluded that samples taken from mixtures might suffice, since primary colors would be concomitantly analyzed.
The present study sought to expand on and confirm the already available information on the painting materials used by the Venetian artist Guido Cadorin (1892–1976). A multi-analytical approach was employed in the study of six tempera grassa easel paintings and one casein tempera on a panel signed by the artist and belonging to the International Gallery of Modern Art Ca’ Pesaro in Venice, Italy, which dated from 1921 to 1951. The aim of the research was to identify the painting materials, observe the evolution of the color palette through time and assess the state of conservation. Non-invasive imaging and/or spectroscopic techniques were employed, such as hyperspectral imaging spectroscopy (HSI) and Raman spectroscopy. Microsamples were also collected from the edges and detached areas of the canvases that were studied through three non-destructive techniques, namely optical microscopy (OM), energy dispersive x-ray fluorescence spectrometry (EDXRF) and attenuated total reflection fourier transform infrared spectroscopy (ATR-FTIR), and one destructive technique, namely gas chromatography-mass spectrometry (GC/MS). The results allowed the inference of the color palette used to render the artist’s paints, composition of the preparation layer, and characterization of the binding media and varnish layers. Moreover, the state of conservation of the artworks was determined. Thus, the outcome of this research enriches the painter’s profile and might aid the International Gallery of Modern Art Ca’ Pesaro in Venice, Italy in the planning of future conservation treatments in accordance with the guidelines of good practices in art conservation.
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.
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