A novel centralization method for pipe image stitching

Salaheddin Hosseinzadeh, William Jackson, Dayi Zhang, Liam McDonald, Gordon Dobie, Graeme West, Charles Norman MacLeod

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
80 Downloads (Pure)


The creation of unwrapped stitched images of pipework internal surfaces is being increasingly used to augment routine visual inspection. A significant challenge to the creation of these stitched images is the need to estimate the pose and position of the camera for each frame, which is often alleviated through the use of a mechanical centralizer to ensure the camera is held in the center of the pipe. This article proposes a novel method for image centralization and pose estimation, which is particularly beneficial to circumstances where mechanical centralization is impractical. The approach involves post-inspection centralization of the captured video, by first estimating the probe’s position relative to the pipe, using an integrated laser ring projector combined with the camera sensor, and then using this position to unwrap the image, so it produces an undistorted view of the pipe interior (equivalent to unwrapping a centralized view). These unwrapped images are then stacked to produce a stitched image of the pipe interior. In this paper pose estimation was successfully demonstrated to have a 90% confidence interval of ±0.5 mm and ±0.5° in translation and rotation changes. This pose estimation is then used to create stitched images for both a visual test card image mounted inside a pipe and an aluminum pipe sample with artificial defects, in both cases demonstrating near equivalent results to those obtained using traditional mechanical centralization.
Original languageEnglish
Pages (from-to)11889-11898
Number of pages10
JournalIEEE Sensors Journal
Issue number10
Early online date19 Oct 2020
Publication statusPublished - 15 May 2021


  • remmote visual inspection
  • depth image-based rendering
  • photogrammetry
  • image unwrapping


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