DOI : https://doi.org/10.18517/ijaseit.10.1.8865

Estimating Damaged Volume of Historic Pagodas in Bagan after Earthquake using 3D Hough Transform

Thida Aung (1), Myint Myint Sein (2)
(1) Faculty of Computer Science, University of Computer Studies, Yangon, Myanmar
(2) Geographic Information System Lab, University of Computer Studies, Yangon, No. (4) Road, Shwe Pyi Thar, Yangon, 11411, Myanmar
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How to cite (IJASEIT) :
Aung, Thida, and Myint Myint Sein. “Estimating Damaged Volume of Historic Pagodas in Bagan After Earthquake Using 3D Hough Transform”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 1, Feb. 2020, pp. 90-97, doi:10.18517/ijaseit.10.1.8865.
Citation Format :
On 24th August 2016, the magnitude of a 6.8 earthquake struck in Bagan from the depth of 52 miles. This earthquake caused much damage in historic pagodas in Bagan, one of the archeological houses in Asia. Analyzing the affected areas is an essential task for the restoration and reconstruction of historic buildings after a disaster. Traditional methods of detecting damage to buildings focus on detecting 2D changes (i.e., only the appearance of the image), but the 2D information provided by the image is not sufficient when it involves detecting damage to buildings is often not precise. For finding out the solution, a method of 3D change detection is needed for estimating the volumes of damaged pagodas after the earthquake. The proposed system aims at producing a quick assessment of the damaged pagodas accurately and correctly. This system estimates the damaged volume of the pagoda based on the nature of the 3D point clouds. Post-earthquake photos are taken using an anonymous aircraft (UAV) and point cloud data is generated using VisualSFM software. The 3D Hough transform is used to find the intersection of the tower vertex and the 3D vertex at the line boundary. Besides, the proposed system can detect the reformed structure of the entire pagoda. The results show that the proposed approach facilitates the automated 3D detection of damaged pagodas and is a time-saving method for estimating the volume of damage caused to precious historic pagodas after a disaster.

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