Mr. Jianghong Zhao Profile

Jianghong Zhao

at Wuhan Univ

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Proceedings Article | 16 October 2009 Paper

Ancient architecture point cloud data triangulation based on algorithm integration with the subdivision of the grid and tangent plane projection

Jianghong Zhao, Yanmin Wang, Xueyan Hu

Proceedings Volume 7492, 74922H (2009) https://doi.org/10.1117/12.837343

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With the development of Terrestrial 3D Laser-scanning technology, as the one of main methods of earth observing architecture, Terrestrial 3D Laser-scanning technology is increasingly widely applied in the field of ancient architecture protection. Triangulating a set of scattered 3D points is a common approach but a difficult problem to surface reconstruction from unorganized point clouds. Because the amount of point cloud data of ancient architecture is very large and the surface of ancient architecture is very complex comparing to reverse engineering field, Universal triangulation algorithms are inefficient and ineffective for complex surface. On the basis of full analysis of the characteristics of the ancient buildings, a modified surface projection-based triangulation algorithm was proposed in this article, which integrated with the subdivision of the grid by K-D tree and tangent plane projection triangulation. The algorithm was used in a real project. Experiments show that the method is more efficient and effective and support for the 3D model reconstruction of ancient buildings is provided.

Proceedings Article | 29 December 2008 Paper

Ancient architecture point cloud data segmentation based on modified fuzzy C-means clustering algorithm

Jianghong Zhao, Deren Li, Yanmin Wang

Proceedings Volume 7285, 72851I (2008) https://doi.org/10.1117/12.815420

KEYWORDS: Clouds, Fuzzy logic, Image segmentation, 3D modeling, Buildings, Feature extraction, Reverse modeling, Laser applications, Reconstruction algorithms, Surface properties

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Segmentation of Point cloud data is a key but difficult problem for architecture 3D reconstruction. Because compared to reverse engineering, there are more noise in ancient architecture point cloud data of edge because of mirror reflection and the traditional methods are hard that is not fuzzy in the preceding part of this paper, these methods can't embody the case of the points of borderline belonging two regions and it is difficult to satisfy demands of segmentation of ancient architecture point cloud data. Ancient architecture is mostly composed of columniation, plinth, arch, girder and tile on specifically order. Each of the component's surfaces is regular and smooth and belongingness of borderline points is very blurry. According to the character the author proposed a modified Fuzzy C-means clustering (MFCM) algorithm, which is used to add geometrical information during clustering. In addition this method improves belongingness constraints to avoid influence of noise on the result of segmentation. The algorithm is used in the project "Digital surveying of ancient architecture--- Forbidden City". Experiments show that the method is a good anti-noise, accuracy and adaptability and greater degree of human intervention is reduced. After segmentation internal point and point edge can be districted according membership of every point, so as to facilitate the follow-up to the surface feature extraction and model identification, and effective support for the three-dimensional model of the reconstruction of ancient buildings is provided.

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