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 |
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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. 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.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2020.3031637</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>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</subject><ispartof>IEEE sensors journal, 2021-05, Vol.21 (10), p.11889-11898</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c336t-a303256a6b2e5c1a7921bf6acfc136b7b8a8f5ac451b958470ffd6cefd4216f3</citedby><cites>FETCH-LOGICAL-c336t-a303256a6b2e5c1a7921bf6acfc136b7b8a8f5ac451b958470ffd6cefd4216f3</cites><orcidid>0000-0003-3972-5917 ; 0000-0003-0884-6070 ; 0000-0002-1360-4722 ; 0000-0001-6253-5287 ; 0000-0003-4611-4161 ; 0000-0003-4364-9769</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9229507$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9229507$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hosseinzadeh, Salaheddin</creatorcontrib><creatorcontrib>Jackson, William</creatorcontrib><creatorcontrib>Zhang, Dayi</creatorcontrib><creatorcontrib>McDonald, Liam</creatorcontrib><creatorcontrib>Dobie, Gordon</creatorcontrib><creatorcontrib>West, Graeme</creatorcontrib><creatorcontrib>MacLeod, Charles</creatorcontrib><title>A Novel Centralization Method for Pipe Image Stitching</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><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.</description><subject>Aluminum</subject><subject>Cameras</subject><subject>Confidence intervals</subject><subject>depth image-based rendering</subject><subject>Equivalence</subject><subject>image unwrapping</subject><subject>Inspection</subject><subject>photogrammetry</subject><subject>Pipework</subject><subject>Pose estimation</subject><subject>Position sensing</subject><subject>post inspection centralization</subject><subject>Probes</subject><subject>Remote visual inspection</subject><subject>Robot vision systems</subject><subject>Stitching</subject><subject>Test cards</subject><subject>Visualization</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMFOAjEQhhujiYg-gPHSxPNip922u0dCEDGIJnDw1nRLCyWwxW4x0ad3NxBPM4fv_2fyIXQPZABAyqfXxXg-oISSASMMBJMXqAecFxnIvLjsdkaynMnPa3TTNFtCoJRc9pAY4nn4tjs8snWKeud_dfKhxm82bcIKuxDxhz9YPN3rtcWL5JPZ-Hp9i66c3jX27jz7aPk8Xo5estn7ZDoazjLDmEiZbp-hXGhRUcsNaFlSqJzQxhlgopJVoQvHtck5VCUvckmcWwlj3SqnIBzro8dT7SGGr6NtktqGY6zbi4py4AVnUuYtBSfKxNA00Tp1iH6v448Cojo7qrOjOjvqbKfNPJwy3lr7z5eUlpxI9gddP1-Z</recordid><startdate>20210515</startdate><enddate>20210515</enddate><creator>Hosseinzadeh, Salaheddin</creator><creator>Jackson, William</creator><creator>Zhang, Dayi</creator><creator>McDonald, Liam</creator><creator>Dobie, Gordon</creator><creator>West, Graeme</creator><creator>MacLeod, Charles</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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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. 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.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSEN.2020.3031637</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3972-5917</orcidid><orcidid>https://orcid.org/0000-0003-0884-6070</orcidid><orcidid>https://orcid.org/0000-0002-1360-4722</orcidid><orcidid>https://orcid.org/0000-0001-6253-5287</orcidid><orcidid>https://orcid.org/0000-0003-4611-4161</orcidid><orcidid>https://orcid.org/0000-0003-4364-9769</orcidid><oa>free_for_read</oa></addata></record> |
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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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