Abstract
Bricks are the vital component of most masonry structures. Their maintenance is critical to the protection of masonry buildings. Terrestrial Light Detection and Ranging (TLidar) systems provide massive point cloud data in an accurate and fast way. TLidar enables us to sample and store the state of a brick surface in a practical way. This article aims to extract individual bricks from an unorganized pile of bricks sampled by a dense point cloud. The method automatically segments and models the individual bricks. The methodology is divided into five main steps: Filter needless points, brick boundary points removal, coarse segmentation using 3D component analysis, planar segmentation and grouping, and brick reconstruction. A novel voting scheme is used to segment the planar patches in an effective way. Brick reconstruction is based on the geometry of single brick and its corresponding nominal size (length, width and height). The number of bricks reconstructed is around 75%. An accuracy assessment is performed by comparing 3D coordinates of the reconstructed vertices to the manually picked vertices. The standard deviations of differences along x, y and z axes are 4.55 mm, 4.53 mm and 4.60 mm, respectively. The comparison results indicate that the accuracy of reconstruction based on the introduced methodology is high and reliable. The work presented in this paper provides a theoretical basis and reference for large scene applications in brick-like structures. Meanwhile, the high-accuracy brick reconstruction lays the foundation for further brick displacement estimation.
Highlights
Terrestrial Light Detection and Ranging (TLidar) provides 3D coordinates of a scene by measuring distances between the scanner’s center and the points on the object surface in a spherical coordinate system
Specific applications for masonry structures containing tiny bricks/stones can be seen in ref. [14], which reported on a point cloud acquired by TLidar used to automatically reconstruct the armor cubes from rubble mound breakwaters
Coarse Segmentation Results Once the edge points are removed, the 3D connected component analysis is implemented to segment brick points
Summary
Terrestrial Light Detection and Ranging (TLidar) provides 3D coordinates of a scene by measuring distances between the scanner’s center and the points on the object surface in a spherical coordinate system. Due to its ability to provide dense and accurate measurements, TLidar has been already successfully applied in various fields related to civil engineering, such as road modeling [1,2], deformation analysis [3,4,5], change detection [6,7,8], cultural heritage [9,10,11] and health monitoring [12,13]. [14], which reported on a point cloud acquired by TLidar used to automatically reconstruct the armor cubes from rubble mound breakwaters. A 3-D morphological method was proposed to change analysis of a beach with seagrass berm using TLS, in which a cost-efficient, accurate and quick tool was used to reconstruct the sand volume in natural and artificial replenished beaches [16]
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