The oriental architecture present in the north-eastern cusp of Sicily is an expression of a mixed-race culture. This hybridization is evident in religious architecture. These buildings have the typological imprint of Catholic churches with Latin cross plans and towered facades, but preserve Arabic traces in the structure of the domes and connections, while also exhibiting Eastern Byzantine traditions in their masonry and rich decorations. The objective of this research is to automate the process of recognizing and segmenting bricks in wall structures to support the analysis of wall fabrics, a crucial task in archaeology and architectural restoration. Our approach processes a point cloud extracted from a facade to identify the wall texture. The results of segmentation can provide statistical information, documenting average brick size, mortar thickness, identification of homogeneous areas, and recognition of masonry sections built with different bricks. Alongside the numerical and abstract information, it is possible to identify the standard morphology of the brick, which also constitutes a sort of digital fingerprint of the church. The size of the bricks influences the geometry and layout of religious architecture. For example, the lateral facades are decorated with intertwined arches entirely composed of bricks. The spacing of the arches, their regularity, and the overall morphology are determined by the size and arrangement of the bricks. Bricks placed on the beds in different ways (stretcher, rowlock stretchers, or heading) determine the repetition or alteration of the geometric-formal modules reiterated in the elevations.
Sicilian Heritage Identity: Between Stereotype and AI-Based Knowledge
The paper investigates how artificial intelligence can be used to visualize and analyze the collective imaginary of a place, focusing on the representation of Sicily through textual descriptions. By applying text-to-image AI models to literary excerpts, the research aims to make explicit the intangible and often stereotypical mental images associated with the Sicilian landscape. The methodology combines textual analysis of selected novels with iterative image generation, examining recurring visual patterns and the influence of lexical structures on the output. Results show that AI tends to reproduce dominant visual archetypes (e.g., horizon lines, central compositions, recurring elements such as sea, boats, or rural landscapes), while struggling to interpret syntactic relationships and complex semantic nuances. The study highlights both the potential of AI as a tool for exploring cultural perception and its limitations in translating abstract, narrative-based descriptions into coherent visual representations.
A Blockchain-Based Solution to Chain (Im)Material Art
This paper investigates the transformation of art in the digital age, focusing on the shift from material artworks to immaterial digital assets and the implications for authorship, authenticity, and value. Building on theoretical frameworks related to reproducibility, simulacra, and digital representation, the study examines the emergence of NFTs as blockchain-based mechanisms designed to restore uniqueness and ownership within infinitely reproducible environments.
Alongside the theoretical analysis, the research proposes and tests a custom blockchain solution based on Ethereum smart contracts to manage and certify ownership of digital artworks. The system associates artworks with unique identifiers and enables transparent tracking of transactions without relying on centralized platforms. The results demonstrate that low-cost, decentralized infrastructures can effectively support authentication and ownership management, while also highlighting the conceptual and economic limitations of current NFT ecosystems.
St. Nicholas of Myra: Reconstruction of the Face between Canon and AI
This study is an ideal continuation of the one presented at REAACH-ID 2021. The results therein obtained are in fact the starting point for new evaluations and for the development of a protocol for the reconstruction of the missing parts in the Byzantine frescoes of St. Nicholas.The research in question aims to carry out, thanks to Artificial Intelligence, digital restorations useful both for the formal and symbolic analysis of Byzantine iconography and for its communication to a wide audience. Four phases describe the research strategy: 1) choice of the case study and the field of investigation; 2) identification of the formal parameters in the processing of the paintings: canon; 3) definition of the work-flow relating to the work of artificial intelligence; 4) application of the study to a specific case and analysis of the obtained results.
Saint Nicholas of Myra. Cataloguing, Identification, and Recognition Through AI
This research elaborates a strategy to guide users and scholars in the Byzantine iconographic world, highlighting the elements that contribute to recognizing the sacred figures represented [2]. It devel-ops two visual approaches: on the one hand, the recognition of faces through a database; on the other hand, the use of artificial intelligence for face recognition. The results of the research can be applied to the development of content for new media edutainment; for the digital restoration of the frescoes; for the communication and enhancement of the asset itself.