Version 1
: Received: 8 September 2023 / Approved: 11 September 2023 / Online: 11 September 2023 (10:12:44 CEST)
How to cite:
Fu, X.; Deng, Y.; Yan, J.; Zhou, J.; Zhou, W.; Liu, P. The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud. Preprints2023, 2023090667. https://doi.org/10.20944/preprints202309.0667.v1
Fu, X.; Deng, Y.; Yan, J.; Zhou, J.; Zhou, W.; Liu, P. The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud. Preprints 2023, 2023090667. https://doi.org/10.20944/preprints202309.0667.v1
Fu, X.; Deng, Y.; Yan, J.; Zhou, J.; Zhou, W.; Liu, P. The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud. Preprints2023, 2023090667. https://doi.org/10.20944/preprints202309.0667.v1
APA Style
Fu, X., Deng, Y., Yan, J., Zhou, J., Zhou, W., & Liu, P. (2023). The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud. Preprints. https://doi.org/10.20944/preprints202309.0667.v1
Chicago/Turabian Style
Fu, X., Wenlong Zhou and Peilin Liu. 2023 "The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud" Preprints. https://doi.org/10.20944/preprints202309.0667.v1
Abstract
The extraction of roof feature lines is an important foundation for realizing large-scale and batch 3D modeling. However, the current traditional point cloud segmentation algorithms do not have satisfactory results in extracting roof feature lines of Chinese traditional residential buildings. In this paper, taking Jingping Village in Western Hunan as an example, we propose a method that combines multiple algorithms based on slope segmentation of roof patches to extract feature lines. Firstly, VDVI and CSF algorithms are used to extract the building and roof point cloud based on the MVS point cloud. Secondly, according to roof features, village buildings are classified, and 3D roof point cloud is projected into 2D regular grid data. Finally, the roof slope is segmented via slope direction, and internal and external feature lines are obtained after refinement through Canny edge detection and Hough straight line detection. Results reveal that this method effectively extracts feature lines of low-building roofs in traditional villages, with slope-based roof surface segmentation accuracy surpassing 99.6%. This method significantly outperforms the RANSAC algorithm and region segmentation algorithm.
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.
