A Novel Multi-Pattern Solder Joint Simultaneous Segmentation Algorithm for PCB Selective Packaging Systems

Huang, Lei; Shen, Shibin; Xie, Fei; Zhao, Jing; Han, Jianing; Feng, Kai

doi:10.1142/s0218001420580057

Cited by 7 publications

(2 citation statements)

References 37 publications

(45 reference statements)

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“…In applications such as the Internet of Things and artificial intelligence, PCB, as a key electronic device, plays a decisive role in the stability of the entire application 1 . To meet the current market demand for more sophisticated and complex electronic circuits, PCBs are moving toward precision, multiple layers, and miniaturization 2 , 3 . In the process of PCB manufacturing, circuit defects are one of the key factors leading to performance degradation.…”

Section: Introductionmentioning

confidence: 99%

Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection

Xia

Liu

et al. 2023

Sci Rep

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To solve the problem of missed and false detection caused by the large number of tiny targets and complex background textures in a printed circuit board (PCB), we propose a global contextual attention augmented YOLO model with ConvMixer prediction heads (GCC-YOLO). In this study, we apply a high-resolution feature layer (P2) to gain more details and positional information of small targets. Moreover, in order to suppress the background noisy information and further enhance the feature extraction capability, a global contextual attention module (GC) is introduced in the backbone network and combined with a C3 module. Furthermore, in order to reduce the loss of shallow feature information due to the deepening of network layers, a bi-directional weighted feature pyramid (BiFPN) feature fusion structure is introduced. Finally, a ConvMixer module is introduced and combined with the C3 module to create a new prediction head, which improves the small target detection capability of the model while reducing the parameters. Test results on the PCB dataset show that GCC-YOLO improved the Precision, Recall, mAP@0.5, and mAP@0.5:0.95 by 0.2%, 1.8%, 0.5%, and 8.3%, respectively, compared to YOLOv5s; moreover, it has a smaller model volume and faster reasoning speed compared to other algorithms.

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Section: Introductionmentioning

confidence: 99%

Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection

Xia

Liu

et al. 2023

Sci Rep

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show abstract

“…At present, most color image segmentation algorithms are obtained by combining the grayscale image segmentation algorithm with the appropriate color space. It is necessary to choose the appropriate method in practice, based on the specific application environment [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Object Region Segmentation Algorithms of PCB Defect Detection

Zhang¹,

Xiao²,

Fu³

2023

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As a core component of electronic products in industrial production, the printed circuit board (PCB) is highly integrated, and carries various electronic components and complex wire layout. Although the PCB has a small size, its defect detection directly affects the quality of circuit board, which is of great significance. This research aimed to study PCB defect detection based on machine vision technology, because the product quality inspection requirements have been continuously increasing in industrial modernization. Whether the object region segmentation algorithms are fast, effective, and accurate directly affects the effects and efficiency of subsequent machine vision defect detection, because object region segmentation is a key step in PCB defect detection. Three types of object region segmentation algorithms, namely, color space threshold segmentation, morphological edge detection segmentation, and K-means clustering segmentation, were studied, and their advantages and disadvantages were analyzed in detail. A suitable algorithm was selected for detection object through experiments, which laid the foundation for better algorithm improvement and segmented object regions quickly and accurately in the defect detection process.

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IC solder joint inspection via generator-adversarial-network based template

Cai

et al. 2021

Machine Vision and Applications

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A Novel Multi-Pattern Solder Joint Simultaneous Segmentation Algorithm for PCB Selective Packaging Systems

Cited by 7 publications

References 37 publications

Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection

Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection

Comparison of Object Region Segmentation Algorithms of PCB Defect Detection

IC solder joint inspection via generator-adversarial-network based template

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