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Automatic Threat Detection for Historic Buildings in Dark Places Based on the Modified OptD Method

Abstrakt

Historic buildings, due to their architectural, cultural, and historical value, are the subject of preservation and conservatory works. Such operations are preceded by an inventory of the object. One of the tools that can be applied for such purposes is Light Detection and Ranging (LiDAR). This technology provides information about the position, reflection, and intensity values of individual points; thus, it allows for the creation of a realistic visualization of the entire scanned object. Due to the fact that LiDAR allows one to ʹseeʹ and extract information about the structure of an object without the need for external lighting or daylight, it can be a reliable and very convenient tool for data analysis for improving safety and avoiding disasters. The main goal of this paper is to present an approach of automatic wall defect detection in unlit sites by means of a modified Optimum Dataset (OptD) method. In this study, the results of Terrestrial Laser Scanning (TLS) measurements conducted in two historic buildings in rooms without daylight are presented. One location was in the basement of the ruins of a medieval tower located in Dobre Miasto, Poland, and the second was in the basement of a century‐old building located at the University of Warmia and Mazury in Olsztyn, Poland. The measurements were performed by means of a Leica C‐10 scanner. The acquired dataset of x, y, z, and intensity was processed by the OptD method. The OptD operates in such a way that within the area of interest where surfaces are imperfect (e.g., due to cracks and cavities), more points are preserved, while at homogeneous surfaces (areas of low interest), more points are removed (redundant information). The OptD algorithm was additionally modified by introducing options to detect and segment defects on a scale from 0 to 3 (0—harmless, 1—to the inventory, 2—requiring repair, 3—dangerous). The survey results obtained proved the high effectiveness of the modified OptD method in the detection and segmentation of the wall defects. The values of area of changes were calculated. The obtained information about the size of the change can be used to estimate the costs of repair, renovation, and reconstruction.

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Autorzy (6)

  • Zdjęcie użytkownika dr inż. Wioleta Błaszczak-Bąk

    Wioleta Błaszczak-Bąk dr inż.

    • Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego 1, 10-719 Olsztyn, Poland
  • Zdjęcie użytkownika  Czesław Suchocki

    Czesław Suchocki

    • Faculty of Civil Engineering Environmental and Geodetic Sciences, Koszalin University of Technology, Śniadeckich 2, 75-453 Koszalin, Poland
  • Zdjęcie użytkownika dr inż. Joanna Janicka

    Joanna Janicka dr inż.

    • Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego 1, 10-719 Olsztyn, Poland
  • Zdjęcie użytkownika  Andrzej Dumalski

    Andrzej Dumalski

    • Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego 1, 10-719 Olsztyn, Poland
  • Zdjęcie użytkownika  Robert Duchnowski

    Robert Duchnowski

    • Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego 1, 10-719 Olsztyn, Poland

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Pełna treść

pobierz publikację
pobrano 11 razy
Wersja publikacji
Accepted albo Published Version
Licencja
Creative Commons: CC-BY otwiera się w nowej karcie

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Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
artykuły w czasopismach
Opublikowano w:
ISPRS International Journal of Geo-Information nr 9, strony 1 - 15,
ISSN: 2220-9964
Język:
angielski
Rok wydania:
2020
Opis bibliograficzny:
Błaszczak-Bąk W., Suchocki C., Janicka J., Dumalski A., Duchnowski R., Sobieraj-Żłobińska A.: Automatic Threat Detection for Historic Buildings in Dark Places Based on the Modified OptD Method// ISPRS International Journal of Geo-Information -Vol. 9,iss. 2 (2020), s.1-15
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/ijgi9020123
Bibliografia: test
  1. Pavlidis, G.; Koutsoudis, A.; Arnaoutoglou, F.; Tsioukas, V.; Chamzas, C. Methods for 3D digitization of Cultural Heritage. J. Cult. Herit. 2007, 8, 93-98. otwiera się w nowej karcie
  2. Fregonese, L.; Barbieri, G.; Biolzi, L.; Bocciarelli, M.; Frigeri, A.; Taffurelli, L. Surveying and Monitoring for Vulnerability Assessment of an Ancient Building. Sensors 2013, 13, 9747-9773. otwiera się w nowej karcie
  3. Del Pozo, S.; Herrero-Pascual, J.; Felipe-García, B.; Hernández-López, D.; Rodríguez-Gonzálvez, P.; González-Aguilera, D. Multispectral Radiometric Analysis of Façades to Detect Pathologies from Active and Passive Remote Sensing. Remote. Sens. 2016, 8, 80. otwiera się w nowej karcie
  4. Corso, J.; Roca, J.; Buill, F. Geometric Analysis on Stone Façades with Terrestrial Laser Scanner Technology. Geosciences 2017, 7, 103. otwiera się w nowej karcie
  5. Alby, E.; Grussenmeyer, P. From point cloud to 3d model, modelling methods based on architectural knowledge applied to fortress of châtel-sur-moselle (france). ISPRS Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci. 2012, 39, 75-80. otwiera się w nowej karcie
  6. Previtali, M.; Barazzetti, L.; Brumana, R.; Cuca, B.; Oreni, D.; Roncoroni, F.; Scaioni, M. Automatic façade modelling using point cloud data for energy-efficient retrofitting. Appl. Geomat. 2014, 6, 95-113. otwiera się w nowej karcie
  7. Altuntas, C.; Yildiz, F.; Scaioni, M. Laser Scanning and Data Integration for Three-Dimensional Digital Recording of Complex Historical Structures: The Case of Mevlana Museum. ISPRS Int. J. Geo-Inf. 2016, 5, 18. otwiera się w nowej karcie
  8. Jo, Y.H.; Hong, S. Three-Dimensional Digital Documentation of Cultural Heritage Site Based on the Convergence of Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry. ISPRS Int. J. Geo-Inf. 2019, 8, 53. otwiera się w nowej karcie
  9. Yastikli, N. Documentation of cultural heritage using digital photogrammetry and laser scanning. J. Cult. Herit. 2007, 8, 423-427. otwiera się w nowej karcie
  10. Du, X.; Zhuo, Y. A point cloud data reduction method based on curvature. In Proceedings of the IEEE 10th International Conference on Computer-Aided Industrial Design & Conceptual Design, Wenzhou, China, 26-29 November 2009; pp. 914-918.
  11. Lin, Y.-J.; Benziger, R.R.; Habib, A. Planar-Based Adaptive Down-Sampling of Point Clouds. Photogramm. Eng. Remote Sens. 2016, 82, 955-966. otwiera się w nowej karcie
  12. Maglo, A.; Lavoue, G.; Dupont, F.; Hudelot, C. 3D Mesh Compression: Survey, Comparisons, and Emerging Trends. ACM Comput. Surv. 2015, 47, 1-44. otwiera się w nowej karcie
  13. Grilli, E.; Menna, F.; Remondino, F. A review of point clouds segmentation and classification algorithms. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2017, 42, 339-344. otwiera się w nowej karcie
  14. Nguyen, A.; Le, B. 3D point cloud segmentation: A survey. In Proceedings of the IEEE Conference on Robotics, Automation and Mechatronics, RAM, Manila, Philippines, 12-15 November 2013. otwiera się w nowej karcie
  15. Suchocki, C.; Błaszczak-Bąk, W. Down-Sampling of Point Clouds for the Technical Diagnostics of Buildings and Structures. Geosciences 2019, 9, 70. otwiera się w nowej karcie
  16. Suchocki, C.; Błaszczak-Bąk, W.; Damięcka-Suchocka, M.; Jagoda, M.; Masiero, A. An example of using the OptD method to optimization of point clouds in the buildings diagnostics. In Proceedings of the 4th Joint International Symposium on Deformation Monitoring (JISDM), Athens, Greece, 15-17 May 2019. otwiera się w nowej karcie
  17. Voegtle, T.; Schwab, I.; Landes, T. Influences of different materials on the measurements of a terrestrial laser scanner (TLS). Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2008, 37, 1061-1066.
  18. Oren, M.; Nayar, S.K. Generalization of Lambert's reflectance model. In Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques-SIGGRAPH '94; ACM: New York, NY, USA, 1994; pp. 239-246. otwiera się w nowej karcie
  19. Suchocki, C.; Katzer, J. Terrestrial laser scanning harnessed for moisture detection in building materials- Problems and limitations. Autom. Constr. 2018, 94, 127-134. otwiera się w nowej karcie
  20. Suchocki, C.; Jagoda, M.; Obuchovski, R.; Šlikas, D.; Sužiedelytė-Visockienė, J. The properties of terrestrial laser system intensity in measurements of technical conditions of architectural structures. Metrol. Meas. Syst. 2018, 25, doi:10.24425/mms.2018.124886. otwiera się w nowej karcie
  21. Douglas, D.H.; Peucker, T.K. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartogr. Int. J. Geogr. Inf. Geovis. 1973, 10, 112-122. otwiera się w nowej karcie
  22. Visvalingam, M.; Whyatt, J.D. Line generalisation by repeated elimination of points. Cartogr. J. 1993, 30, 46- 51. otwiera się w nowej karcie
  23. Opheim, H. Smoothing a digitized curve by data reduction methods. Eurograph. Assoc. 1981, doi:10.2312/eg.19811012. otwiera się w nowej karcie
  24. Blaszczak-Bak, W. New Optimum Dataset method in LiDAR processing. Acta Geodyn. Geomater. 2016, 13, 381-388. otwiera się w nowej karcie
  25. Błaszczak-Bąk, W.; Sobieraj-Żłobińska, A.; Kowalik, M. The OptD-multi method in LiDAR processing. Meas. Sci. Technol. 2017, 28, 75009. otwiera się w nowej karcie
Weryfikacja:
Politechnika Gdańska

wyświetlono 28 razy

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