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. They 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 and exhibit 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 the 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 will be 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 decorated with bricks. The spacing of the arches, the regularity and the overall morphology are determined by the size and arrangement of the bricks. The 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.

Automated Recognition and Segmentation of Bricks Wall in Sicilian Monasteries / Arena, Marinella; Lax, Gianluca. - (2026), pp. 615-629. [10.1007/978-3-032-04711-3_35]

Automated Recognition and Segmentation of Bricks Wall in Sicilian Monasteries

Arena, Marinella;Lax, Gianluca
2026-01-01

Abstract

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. They 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 and exhibit 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 the 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 will be 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 decorated with bricks. The spacing of the arches, the regularity and the overall morphology are determined by the size and arrangement of the bricks. The 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.
2026
9783032047106
9783032047113
Artificial intelligence · Python · Point cloud processing · Pattern recognition · Architectural restoration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/163466
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