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 (2021) A novel centralization method for pipe image stitching. IEEE Sensors Journal, 21 (10). pp. 11889-11898. ISSN 1530-437X (https://doi.org/10.1109/JSEN.2020.3031637)

[thumbnail of Hosseinzadeh -etal-IEEESJ-2020-A-novel-centralization-method-for-pipe]
Preview
 Text. Filename: 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.

ORCID iDs

Hosseinzadeh, Salaheddin, Jackson, William ORCID logoORCID: https://orcid.org/0000-0002-1360-4722, Zhang, Dayi ORCID logoORCID: https://orcid.org/0000-0003-4611-4161, McDonald, Liam, Dobie, Gordon ORCID logoORCID: https://orcid.org/0000-0003-3972-5917, West, Graeme ORCID logoORCID: https://orcid.org/0000-0003-0884-6070 and MacLeod, Charles Norman ORCID logoORCID: https://orcid.org/0000-0003-4364-9769;
  • Item type:Article
    ID code:74309
    Dates:
    Date
    Event
    15 May 2021
    Published
    19 October 2020
    Published Online
    13 October 2020
    Accepted
    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:28 Apr 2022 00:35
    URI:https://strathprints.strath.ac.uk/id/eprint/74309
CORE (COnnecting REpositories)