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Automatic Morphologic Analysis of Quasi‐Periodic Masonry Walls from LiDAR
Author(s) -
Riveiro Belén,
Lourenço Paulo B.,
Oliveira Daniel V.,
GonzálezJorge Higinio,
Arias Pedro
Publication year - 2016
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12145
Subject(s) - masonry , point cloud , segmentation , lidar , computer science , block (permutation group theory) , point (geometry) , computer vision , image segmentation , artificial intelligence , remote sensing , geology , engineering , structural engineering , mathematics , geometry
Abstract This article presents a novel segmentation algorithm that allows the automatic segmentation of masonry blocks from a 3D point cloud acquired with LiDAR technology, for both stationary and mobile devices. The point cloud segmentation algorithm is based on a 2.5D approach that creates images based on the intensity attribute of LiDAR systems. Image processing algorithms based on an improvement of the marked‐controlled watershed was successfully used to produce the automatic segmentation of the point cloud in the 3D space isolating each individual stone block. Finally, morphologic analysis in two case studies has been carried out. The morphologic analysis provides information about the assemblage of masonry pieces, which is valuable for the structural evaluation of masonry buildings.