PreprintArticleVersion 1This version is not peer-reviewed
Change Detection Techniques in Dense Point Clouds for Cultural Heritage Preservation: The Case Study of the San Pietro Barisano Bell Tower in Matera, Italy
Version 1
: Received: 31 August 2024 / Approved: 2 September 2024 / Online: 2 September 2024 (16:59:48 CEST)
How to cite:
Fattore, C.; Porcari, S.; Priore, A.; Porcari, V. D. Change Detection Techniques in Dense Point Clouds for Cultural Heritage Preservation: The Case Study of the San Pietro Barisano Bell Tower in Matera, Italy. Preprints2024, 2024090113. https://doi.org/10.20944/preprints202409.0113.v1
Fattore, C.; Porcari, S.; Priore, A.; Porcari, V. D. Change Detection Techniques in Dense Point Clouds for Cultural Heritage Preservation: The Case Study of the San Pietro Barisano Bell Tower in Matera, Italy. Preprints 2024, 2024090113. https://doi.org/10.20944/preprints202409.0113.v1
Fattore, C.; Porcari, S.; Priore, A.; Porcari, V. D. Change Detection Techniques in Dense Point Clouds for Cultural Heritage Preservation: The Case Study of the San Pietro Barisano Bell Tower in Matera, Italy. Preprints2024, 2024090113. https://doi.org/10.20944/preprints202409.0113.v1
APA Style
Fattore, C., Porcari, S., Priore, A., & Porcari, V. D. (2024). Change Detection Techniques in Dense Point Clouds for Cultural Heritage Preservation: The Case Study of the San Pietro Barisano Bell Tower in Matera, Italy. Preprints. https://doi.org/10.20944/preprints202409.0113.v1
Chicago/Turabian Style
Fattore, C., Arcangelo Priore and Vito Domenico Porcari. 2024 "Change Detection Techniques in Dense Point Clouds for Cultural Heritage Preservation: The Case Study of the San Pietro Barisano Bell Tower in Matera, Italy" Preprints. https://doi.org/10.20944/preprints202409.0113.v1
Abstract
This study examines change detection techniques in dense point clouds for the purpose of Cultural Heritage preservation, with a particular focus on the San Pietro Barisano Bell Tower in Matera, Italy. Dense point clouds, obtained via advanced laser scanning, offer detailed 3D representations of heritage structures, facilitating the precise monitoring changes over time. The investigation uses a variety of change detection algorithms, including the Iterative Closest Point (ICP) algorithm, which is renowned for its robust registration capabilities in aligning point clouds with high accuracy. The combination of ICP with deviation analysis and feature-based methods allows for the effective identification of alterations, including deformations, material loss, and surface degradation. This methodology establishes a comprehensive framework for the monitoring of Cultural Heritage, thereby enabling timely and targeted preservation efforts. The results emphasise the substantial contribution of dense point cloud analysis to the enhancement of heritage management and the safeguarding of vulnerable architectural sites.
Keywords
Change detection; Dense Point Cloud; Cultural Heritage
Subject
Engineering, Architecture, Building and Construction
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
