A Novel Centralization Method for Pipe Image Stitching

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 allevia...

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Veröffentlicht in:IEEE sensors journal 2021-05, Vol.21 (10), p.11889-11898
Hauptverfasser: Hosseinzadeh, Salaheddin, Jackson, William, Zhang, Dayi, McDonald, Liam, Dobie, Gordon, West, Graeme, MacLeod, Charles
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container_end_page 11898
container_issue 10
container_start_page 11889
container_title IEEE sensors journal
container_volume 21
creator Hosseinzadeh, Salaheddin
Jackson, William
Zhang, Dayi
McDonald, Liam
Dobie, Gordon
West, Graeme
MacLeod, Charles
description 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.
doi_str_mv 10.1109/JSEN.2020.3031637
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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. 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subjects Aluminum
Cameras
Confidence intervals
depth image-based rendering
Equivalence
image unwrapping
Inspection
photogrammetry
Pipework
Pose estimation
Position sensing
post inspection centralization
Probes
Remote visual inspection
Robot vision systems
Stitching
Test cards
Visualization
title A Novel Centralization Method for Pipe Image Stitching
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