A fast and automated method for extracting tunnel cross-sections using terrestrial laser scanned data

Soohee Han, Hyungsig Cho, Sangmin Kim, Joon Heo

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)

Abstract

In tunnel construction, overcut along with undercut estimation is one of the most important factors to be considered before proceeding to the next operation. It is currently analyzed based on sparsely sampled points surveyed using a total station, but not much time is allowed for surveying and analyzing for economic reasons. A fast and automated method is presented to extract dense tunnel cross-sections using Terrestrial Laser Scanner (TLS) data. A 3D point cloud acquired from the TLS is converted to a two-dimensional planar image and skeletonized to estimate the tunnel centerline. Cross-sections are extracted orthogonal to the centerline. To evaluate the performance of the proposed method, it was applied to actual tunnel data and compared with the results from a conventional method using a total station. In the results, the cross-sections were extracted at center points corresponding to those of the conventional method. The proposed method proved itself to have advantages in terms of its ability to offer a detailed description and improve the efficiency of the processing time.

Original languageEnglish
Pages1013-1018
Number of pages6
DOIs
Publication statusPublished - 2011
Event28th International Symposium on Automation and Robotics in Construction, ISARC 2011 - Seoul, Korea, Republic of
Duration: 2011 Jun 292011 Jul 2

Other

Other28th International Symposium on Automation and Robotics in Construction, ISARC 2011
CountryKorea, Republic of
CitySeoul
Period11/6/2911/7/2

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Building and Construction
  • Computer Vision and Pattern Recognition

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