Search Results (3)

Mithraea, religious Roman buildings, are very common in Italian archeological sites. There are sixteen in Ostia Antica (Rome, Italy)The poor state of conservation, due to the intrinsic environmental conditions, characterized them: they consist of open-air museums and caves simultaneously. These places of worship are characterized by the presence of heterogeneous materials, such as wall building materials (bricks and mortars) and others used for furnishings and fittings. This increases the risk of accelerated damage because the materials ‘rheology is different. Here, a full petrographic-mineralogical characterization with polarized light microscopy (PLM), X-ray diffraction (XRD), scanning electron microscope with energy dispersive X-ray (SEM-EDS) and isotopic analysis (δ13C, δ18O) is carried out on materials like travertine, marble, pumice, ceramic, and wall-building materials in “Casa di Diana” Mithraeum (Ostia Antica). Their characterization gives provenance information as well as conservation and restoration purposes. The prevalence of siliciclastic or carbonate components discriminates between red and yellow bricks, as well as different textures and minerals in the aggregate of the red ones. The mortars are typically pozzolanic, and the aggregate is mostly made up of black and red pozzolanic clasts. In the altar, apse, and aedicule, which constitute the principal place of the Mithraeum, a variety of materials used for the ornamental purpose are represented by pumices, travertine, marble, and limestone. The altar material, catalogued as marble, resulted in being a limestone coated with a white pigment. Full article

From the 1950s and 1960s of the last century, a parish church dating back to the 6th century AD was identified during reclamation works of Valle Pega. The archaeological investigation allowed the recovery of the parish and the attached baptistery, as well as some tombs closely connected to the church. Following the excavation, it was possible to collect some samples of bricks and mortars in order to identify the different compositions of the materials used for the construction of the parish. All the samples were analyzed through optical microscopy, X-ray powder diffractometric analysis and observation through scanning electron microscope. Thanks to the investigations carried out on the samples, it was possible to hypothesize the different construction phases and the different materials used and to identify the firing temperatures at which the bricks were built. Full article

In this paper we introduce a novel machine learning-based fully automatic approach for the semantic analysis and documentation of masonry wall images, performing in parallel automatic detection and virtual completion of occluded or damaged wall regions, and brick segmentation leading to an accurate model of the wall structure. For this purpose, we propose a four-stage algorithm which comprises three interacting deep neural networks and a watershed transform-based brick outline extraction step. At the beginning, a U-Net-based sub-network performs initial wall segmentation into brick, mortar and occluded regions, which is followed by a two-stage adversarial inpainting model. The first adversarial network predicts the schematic mortar-brick pattern of the occluded areas based on the observed wall structure, providing in itself valuable structural information for archeological and architectural applications. The second adversarial network predicts the pixels’ color values yielding a realistic visual experience for the observer. Finally, using the neural network outputs as markers in a watershed-based segmentation process, we generate the accurate contours of the individual bricks, both in the originally visible and in the artificially inpainted wall regions. Note that while the first three stages implement a sequential pipeline, they interact through dependencies of their loss functions admitting the consideration of hidden feature dependencies between the different network components. For training and testing the network a new dataset has been created, and an extensive qualitative and quantitative evaluation versus the state-of-the-art is given. The experiments confirmed that the proposed method outperforms the reference techniques both in terms of wall structure estimation and regarding the visual quality of the inpainting step, moreover it can be robustly used for various different masonry wall types. Full article