3D reconstruction and defect pattern recognition of bonding wire based on stereo vision
Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging. Image‐processing‐based methods do not provide a detailed evaluation of the three‐dimensional defects of the bonding wire. Therefore, a method of 3D reconstruction a...
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| Published in: | CAAI Transactions on Intelligence Technology Vol. 9; no. 2; pp. 348 - 364 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Beijing
John Wiley & Sons, Inc
01.04.2024
Wiley |
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| ISSN: | 2468-2322, 2468-6557, 2468-2322 |
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| Abstract | Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging. Image‐processing‐based methods do not provide a detailed evaluation of the three‐dimensional defects of the bonding wire. Therefore, a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision, which can achieve non‐destructive detection of bonding wire defects is proposed. The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires. Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface, a point cloud segmentation method based on spatial surface feature detection (SFD) was proposed. SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process. Furthermore, in the defect detection process, a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires. The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires. The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires, and the average accuracy of defect recognition is 96.47%, which meets the production requirements of bonding wire defect detection. |
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| AbstractList | Abstract Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging. Image‐processing‐based methods do not provide a detailed evaluation of the three‐dimensional defects of the bonding wire. Therefore, a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision, which can achieve non‐destructive detection of bonding wire defects is proposed. The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires. Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface, a point cloud segmentation method based on spatial surface feature detection (SFD) was proposed. SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process. Furthermore, in the defect detection process, a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires. The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires. The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires, and the average accuracy of defect recognition is 96.47%, which meets the production requirements of bonding wire defect detection. Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging. Image‐processing‐based methods do not provide a detailed evaluation of the three‐dimensional defects of the bonding wire. Therefore, a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision, which can achieve non‐destructive detection of bonding wire defects is proposed. The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires. Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface, a point cloud segmentation method based on spatial surface feature detection (SFD) was proposed. SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process. Furthermore, in the defect detection process, a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires. The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires. The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires, and the average accuracy of defect recognition is 96.47%, which meets the production requirements of bonding wire defect detection. |
| Author | Yu, Naigong Xu, Qiao Firdaous, Essaf Sie, Ouattara Li, Hongzheng |
| Author_xml | – sequence: 1 givenname: Naigong surname: Yu fullname: Yu, Naigong email: yunaigong@bjut.edu.cn organization: Ministry of Education – sequence: 2 givenname: Hongzheng orcidid: 0000-0001-6535-596X surname: Li fullname: Li, Hongzheng organization: Ministry of Education – sequence: 3 givenname: Qiao surname: Xu fullname: Xu, Qiao organization: Ministry of Education – sequence: 4 givenname: Ouattara surname: Sie fullname: Sie, Ouattara organization: Université Félix Houphouët‐Boigny – sequence: 5 givenname: Essaf surname: Firdaous fullname: Firdaous, Essaf organization: Ministry of Education |
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| Snippet | Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging. Image‐processing‐based... Abstract Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging.... |
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| StartPage | 348 |
| SubjectTerms | Aircraft Bonding bonding wire Deep learning defect detection Defects Electronic components Feature extraction Image quality Image reconstruction Image segmentation Integrated circuits Manufacturing Methods Pattern recognition point cloud point cloud segmentation Semiconductors Three dimensional models Vision systems Wire |
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| Title | 3D reconstruction and defect pattern recognition of bonding wire based on stereo vision |
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