Laser Scanning Point Cloud Improvement by Implementation of RANSAC for Pipeline Inspection Application

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

  • Cesar Sepulveda-Valdez
  • Oleg Sergiyenko
  • Ruben Alaniz-Plata
  • Jose A. Nunez-Lopez
  • Vera Tyrsa
  • Wendy Flores-Fuentes
  • Julio C. Rodriguez-Quinonez
  • Paolo Mercorelli
  • Marina Kolendovska
  • Vladimir Kartashov
  • Jesus Elias Miranda-Vega
  • Fabian N. Murrieta-Rico

Laser Scanners used for Structural Health Monitoring applications such as Pipelines Structural Inspections normally needs Point Clouds from a large quantity of individual measurements that should be adjusted or post-processed to decrease overall point-cloud errors depending on scanner's characteristics. The posterior adjustment is commonly addressed by different mathematical methods or computational algorithms. According to application requirements methods such as machine learning, signal filtering, or RANSAC algorithms are used. This paper shows the application of an adapted/modify RANSAC algorithm especially suited for the pipeline inspection task. Aiming to increase the percentage of useful data per capture.

OriginalspracheEnglisch
TitelIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
Anzahl der Seiten6
ErscheinungsortPiscataway
VerlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Erscheinungsdatum2023
ISBN (Print)979-8-3503-3183-7
ISBN (elektronisch)979-8-3503-3182-0
DOIs
PublikationsstatusErschienen - 2023
Veranstaltung49th Annual Conference of the IEEE Industrial Electronics Society, 2023: Marina Bay Sands Expo and Convention Centre, Singapore - Marina Bay Sands Expo and Convention Centre, Singapore, Singapur
Dauer: 16.10.202319.10.2023
https://www.iecon2023.org

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Publisher Copyright:
© 2023 IEEE.

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