한국BIM학회 논문집 (Journal of KIBIM)

  • 제10권4호
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  • Pages.32-39
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  • 2020
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  • 2288-1697(pISSN)
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  • 2288-1697(eISSN)
한국BIM학회 (Korean Institute of Building Information Modeling)
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건설현장 적용을 위한 디지털맵 노이즈 제거 알고리즘 성능평가

Performance Evaluation of Denoising Algorithms for the 3D Construction Digital Map

  • 박수열 (한국교통대학교 철도융합시스템공학과) ;
  • 김석 (한국교통대학교 철도인프라시스템공학과)
  • 투고 : 2020.11.10
  • 심사 : 2020.11.11
  • 발행 : 2020.12.31
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초록

In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.

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참고문헌

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