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3D reconstruction and defect pattern recognition of bonding wire based on stereo vision

CAAI Transactions on Intelligence Technology 2024年第2期9卷 348-364页

作者： Naigong Yu Hongzheng Li Qiao Xu Ouattara Sie essaf firdaous Faculty of Information Technology Beijing University of TechnologyBeijingChina Beijing Key Laboratory of Computing Intelligence and Intelligent System Beijing University of TechnologyBeijingChina Engineering Research Center of Digital Community Ministry of EducationBeijingChina College of Robotic UniversitéFélix Houphouët‐BoignyAbidjanCôte d’Ivoire

Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after ***-processing-based methods do not provide a detailed evaluation of the three-dimensional defects of the bonding ***,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 *** contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding *** 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 *** can extract more distinct features from the bonding wire surface during the point cloud segmentation ***,in the defect detection process,a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding *** descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of *** 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.

关键词： bonding wire defect detection point cloud point cloud segmentation

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