3D Segmentation and Analysis for Masonry Bridge Preservation

Abstract. In recent years, laser scanning and other survey techniques have become popular for documenting and preserving architectural and structural heritage, including masonry bridges. These bridges require careful monitoring to ensure proper structural integrity analyses. However, analysing large datasets of complex point clouds can be challenging and time consuming. This research introduces an automated method to quickly assess the geometric characteristics of vault of bridges by means of a simple algorithm purposely developed for this application. The developed methodology was implemented in MATLAB. The main geometric features, such as length, arrow, and span, are extracted, and conditional algorithms classify the vault types based on specific thresholds. The methodology is tested on surveyed masonry bridges coming from a case study: the historical Circumetnea railway bridges in Sicily, Italy. A digital survey campaign was conducted using various survey techniques such as laser scanning and photogrammetry to obtain the vault point clouds. This research represents a step forward from previous methodologies by efficiently segmenting and analysing vaults from point clouds, enabling accurate classification and geometric analysis.