Cultural Heritage Preservation through Multispectral Imaging: Preliminary Results from the IMAGO Project

The IMAGO project aims to develop an innovative system that utilizes Multispectral Imaging and Augmented Reality (AR) techniques for studying and preserving cultural heritage. By employing machine learning algorithms on multispectral images, the system can detect lost original elements and hidden features in cultural artifacts, offering a unique perspective beyond human vision. Here we show some preliminary results related to the multi spectral analysis conducted on three paintings attributed to Cavalier d'Arpino (Giuseppe Cesari) located at the Galleria dell'Accademia Nazionale di San Luca in Rome. Non-invasive and portable techniques such as Energy Dispersive X-ray Fluorescence (ED-XRF) spectrometry, Fiber Optics Reflectance Spectroscopy (FORS), UV fluorescence imaging, and Multispectral (MS) imaging were employed. Preliminary characterization of the pictorial materials was achieved through FORS and ED-XRF analyses, allowing the identi- fication of pigments used for the creation of the three paintings and highlighting similarities and differences in the palette. MS images, acquired between the ultraviolet and near-infrared regions (NIR), revealed significant differences between visible and NIR images with some details of the paintings transparent in the infrared region. Furthermore, data clustering algorithms were applied to the MS images, enabling semantic segmentation and providing extrapolation of salient parts of the artwork and better per- ception of details. The combined results of this work contribute to the preservation and interpretation of cultural heritage and are of paramount importance for the developing of the IMAGO system