Segmenting welding flaws of non-horizontal shape
Rapid detection of distortions formed in the welds of metal has high importance to prevent disasters. Radiography images of the weld have an unlimited number of small defects with diverse shapes. Visual inspection of the weld is a complicated, time-consuming task; and depends on the observers'...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-08-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016821001411 |
| _version_ | 1818900531309969408 |
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| author | Doaa Radi Mohy Eldin A Abo-Elsoud Fahmi Khalifa |
| author_facet | Doaa Radi Mohy Eldin A Abo-Elsoud Fahmi Khalifa |
| author_sort | Doaa Radi |
| collection | DOAJ |
| description | Rapid detection of distortions formed in the welds of metal has high importance to prevent disasters. Radiography images of the weld have an unlimited number of small defects with diverse shapes. Visual inspection of the weld is a complicated, time-consuming task; and depends on the observers' experience. Many computer-aided detection techniques have emerged as an alternative tool for segmenting the flaws of the weld, but none of them could segment alone all types of weld defects. In this paper, we attempt a possible solution and a novel image-based approach to solve the problem of weld defect detection using a data set of X-ray images. We aim to subtract the background and all horizontal defects and segment the non-horizontal flaws. For that, we apply some morphological operations and wiener filter to enhance the image quality; we use two novel filters to segment the non-horizontal defects; finally, we perform a post-processing operation. Our method depends on two convolution processes between the designed filters and the original image to achieve the segmentation process. We tested our approach on a universally available database of 68 images of the weld. Our method achieved high segmentation accuracy with zero errors. We highlighted the academic advancement of our technique by comparing its performance with other methods. Our efficient approach is effortless, applicable in practical segmentation processes of the defects of the weld. In the future, we will dedicate our work to the segmentation of horizontal defects by altering the shape of the two filters. Our method achieves satisfying accuracy; so, it is promising for weld defect detection. The particular contribution of our technique is that it can segment alone all types of weld defects, contrary to traditional weld defect detection methods. The computing time is optimized compared to other algorithms. |
| first_indexed | 2024-12-19T20:05:20Z |
| format | Article |
| id | doaj.art-15682d71016b48b1bf5efff22a4cb4ed |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-12-19T20:05:20Z |
| publishDate | 2021-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-15682d71016b48b1bf5efff22a4cb4ed2022-12-21T20:07:31ZengElsevierAlexandria Engineering Journal1110-01682021-08-0160440574065Segmenting welding flaws of non-horizontal shapeDoaa Radi0Mohy Eldin A Abo-Elsoud1Fahmi Khalifa2Corresponding author.; Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Dakahlyia 35516, EgyptElectronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Dakahlyia 35516, EgyptElectronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Dakahlyia 35516, EgyptRapid detection of distortions formed in the welds of metal has high importance to prevent disasters. Radiography images of the weld have an unlimited number of small defects with diverse shapes. Visual inspection of the weld is a complicated, time-consuming task; and depends on the observers' experience. Many computer-aided detection techniques have emerged as an alternative tool for segmenting the flaws of the weld, but none of them could segment alone all types of weld defects. In this paper, we attempt a possible solution and a novel image-based approach to solve the problem of weld defect detection using a data set of X-ray images. We aim to subtract the background and all horizontal defects and segment the non-horizontal flaws. For that, we apply some morphological operations and wiener filter to enhance the image quality; we use two novel filters to segment the non-horizontal defects; finally, we perform a post-processing operation. Our method depends on two convolution processes between the designed filters and the original image to achieve the segmentation process. We tested our approach on a universally available database of 68 images of the weld. Our method achieved high segmentation accuracy with zero errors. We highlighted the academic advancement of our technique by comparing its performance with other methods. Our efficient approach is effortless, applicable in practical segmentation processes of the defects of the weld. In the future, we will dedicate our work to the segmentation of horizontal defects by altering the shape of the two filters. Our method achieves satisfying accuracy; so, it is promising for weld defect detection. The particular contribution of our technique is that it can segment alone all types of weld defects, contrary to traditional weld defect detection methods. The computing time is optimized compared to other algorithms.http://www.sciencedirect.com/science/article/pii/S1110016821001411Computer-aided detectionWeldDefectSegmentationBackgroundSubtraction |
| spellingShingle | Doaa Radi Mohy Eldin A Abo-Elsoud Fahmi Khalifa Segmenting welding flaws of non-horizontal shape Alexandria Engineering Journal Computer-aided detection Weld Defect Segmentation Background Subtraction |
| title | Segmenting welding flaws of non-horizontal shape |
| title_full | Segmenting welding flaws of non-horizontal shape |
| title_fullStr | Segmenting welding flaws of non-horizontal shape |
| title_full_unstemmed | Segmenting welding flaws of non-horizontal shape |
| title_short | Segmenting welding flaws of non-horizontal shape |
| title_sort | segmenting welding flaws of non horizontal shape |
| topic | Computer-aided detection Weld Defect Segmentation Background Subtraction |
| url | http://www.sciencedirect.com/science/article/pii/S1110016821001411 |
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