A novel centralization method for pipe image stitching
Hosseinzadeh, Salaheddin and Jackson, William and Zhang, Dayi and McDonald, Liam and Dobie, Gordon and West, Graeme and MacLeod, Charles Norman (2020) A novel centralization method for pipe image stitching. IEEE Sensors Journal. ISSN 1530-437X
|
Text (Hosseinzadeh -etal-IEEESJ-2020-A-novel-centralization-method-for-pipe)
Hosseinzadeh_etal_IEEESJ_2020_A_novel_centralization_method_for_pipe.pdf Accepted Author Manuscript Download (1MB)| Preview |
Abstract
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.
Creators(s): |
Hosseinzadeh, Salaheddin, Jackson, William ![]() ![]() ![]() ![]() ![]() | Item type: | Article |
---|---|
ID code: | 74309 |
Notes: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | remmote visual inspection, depth image-based rendering, photogrammetry, image unwrapping, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering |
Subjects: | Technology > Electrical engineering. Electronics Nuclear engineering |
Department: | Faculty of Engineering > Electronic and Electrical Engineering Strategic Research Themes > Energy Strategic Research Themes > Advanced Manufacturing and Materials |
Depositing user: | Pure Administrator |
Date deposited: | 20 Oct 2020 09:09 |
Last modified: | 21 Jan 2021 12:26 |
Related URLs: | |
URI: | https://strathprints.strath.ac.uk/id/eprint/74309 |
Export data: |