Discontinuities detection in welded joints based on inverse surface thresholding
Automated detection of welding defects in radiographic images becomes nontrivial when uneven illumination, contrast and noise are present. In this paper, a new approach using surface thresholding method is proposed to detect defects in radiographic images of welding joints. In the first stage, sever...
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my.um.eprints.230452019-11-18T04:10:31Z http://eprints.um.edu.my/23045/ Discontinuities detection in welded joints based on inverse surface thresholding Yazid, Haniza Arof, Hamzah Yazid, Hafizal Ahmad, Sahrim Mohamed, Abdul Aziz Ahmad, Fauzan TK Electrical engineering. Electronics Nuclear engineering Automated detection of welding defects in radiographic images becomes nontrivial when uneven illumination, contrast and noise are present. In this paper, a new approach using surface thresholding method is proposed to detect defects in radiographic images of welding joints. In the first stage, several image processing techniques namely fuzzy c means clustering, region filling, mean filtering, edge detection, Otsu thresholding, and morphological operations method are utilized to locate the area where defects might exist. This is followed by the construction of the inverse thresholding surface and its implementation to locate defects in the identified area. The proposed method was tested on 60 radiographic images and it obtained 94.6% sensitivity. Its performance is compared to that of the watershed segmentation, which obtained 69.6%. © 2011 Elsevier Ltd. Elsevier 2011 Article PeerReviewed Yazid, Haniza and Arof, Hamzah and Yazid, Hafizal and Ahmad, Sahrim and Mohamed, Abdul Aziz and Ahmad, Fauzan (2011) Discontinuities detection in welded joints based on inverse surface thresholding. NDT & E International, 44 (7). pp. 563-570. ISSN 0963-8695 https://doi.org/10.1016/j.ndteint.2011.06.002 doi:10.1016/j.ndteint.2011.06.002 |
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TK Electrical engineering. Electronics Nuclear engineering Yazid, Haniza Arof, Hamzah Yazid, Hafizal Ahmad, Sahrim Mohamed, Abdul Aziz Ahmad, Fauzan Discontinuities detection in welded joints based on inverse surface thresholding |
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Automated detection of welding defects in radiographic images becomes nontrivial when uneven illumination, contrast and noise are present. In this paper, a new approach using surface thresholding method is proposed to detect defects in radiographic images of welding joints. In the first stage, several image processing techniques namely fuzzy c means clustering, region filling, mean filtering, edge detection, Otsu thresholding, and morphological operations method are utilized to locate the area where defects might exist. This is followed by the construction of the inverse thresholding surface and its implementation to locate defects in the identified area. The proposed method was tested on 60 radiographic images and it obtained 94.6% sensitivity. Its performance is compared to that of the watershed segmentation, which obtained 69.6%. © 2011 Elsevier Ltd. |
format |
Article |
author |
Yazid, Haniza Arof, Hamzah Yazid, Hafizal Ahmad, Sahrim Mohamed, Abdul Aziz Ahmad, Fauzan |
author_facet |
Yazid, Haniza Arof, Hamzah Yazid, Hafizal Ahmad, Sahrim Mohamed, Abdul Aziz Ahmad, Fauzan |
author_sort |
Yazid, Haniza |
title |
Discontinuities detection in welded joints based on inverse surface thresholding |
title_short |
Discontinuities detection in welded joints based on inverse surface thresholding |
title_full |
Discontinuities detection in welded joints based on inverse surface thresholding |
title_fullStr |
Discontinuities detection in welded joints based on inverse surface thresholding |
title_full_unstemmed |
Discontinuities detection in welded joints based on inverse surface thresholding |
title_sort |
discontinuities detection in welded joints based on inverse surface thresholding |
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Elsevier |
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2011 |
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http://eprints.um.edu.my/23045/ https://doi.org/10.1016/j.ndteint.2011.06.002 |
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1651867391631556608 |