| Citation: |
WANG Li, XIA Xuan. Infrared Image Segmentation Method of Circuit Board Based on GAN-SUNet[J]. Infrared Technology , 2025, 47(4): 493-500.
|
Infrared images can directly reflect the temperature of a circuit board and its changes. To address the challenge of accurately locating chips on infrared images of circuit boards, this paper proposes a segmentation method based on the GAN-SUNet model. The SUNet model is improved from the UNet model by introducing a spatial pyramid pooling (SPP) module, modifying the loss function, and reducing the number of convolution cores to enhance detection accuracy and network speed. First, a GAN is used to learn and train on collected infrared circuit board data to generate simulated infrared images and expand the dataset. Then, the generated dataset is used to train the SUNet model, and model parameters are adjusted to improve verification accuracy. Finally, the trained model is used to identify, detect, and segment chips on circuit boards, thereby achieving chip localization in infrared images. Experimental results show that for infrared image segmentation of circuit boards, the GAN-SUNet model achieves an average intersection and merging ratio of 93.77%, effectively reducing the burden of manual chip localization and providing strong support for subsequent chip temperature data processing.
| [1] |
SHI L, ZHOU Z, JIA H, et al. Fault diagnosis of functional circuit in avionics system based on BPNN[C]//2019 Prognostics and System Health Management Conference (PHM-Qingdao) of IEEE, 2019: 1-5.
|
| [2] |
ZHENG T, WANG Z, TAN C, et al. Research on fault prediction and diagnosis method of PCB circuit[C]//2020 International Conference on Artificial Intelligence and Computer Engineering (ICAICE) of IEEE, 2020: 387-390.
|
| [3] |
曾佩佩. 基于主动轮廓模型的PCB红外图像分割[D]. 天津: 中国民航大学, 2014.
ZENG Peipei. PCB Infrared Image Segmentation Based on Active Contour[D]. Tianjin: Civil Aviation University of China, 2014.
|
| [4] |
吕昂, 陈怡, 方晋甬, 等. 基于红外热成像的电路板载器件故障检测[J]. 激光与红外, 2018, 48(5): 579-584. DOI: 10.3969/j.issn.1001-5078.2018.05.008
LV Ang, CHEN Yi, FANG Jinyong, et al. Defect detection for circuit-board-mounted devices based on infrared imaging[J]. Laser & Infrared, 2018, 48(5): 579-584. DOI: 10.3969/j.issn.1001-5078.2018.05.008
|
| [5] |
DONG Z, CHEN L. Image registration in PCB fault detection based on infrared thermal imaging[C]//2019 Chinese Control Conference (CCC) of IEEE, 2019: 4819-4823.
|
| [6] |
郝建新, 王力. 基于改进脉冲耦合神经网络的电路板红外图像分割[J]. 激光与红外, 2020, 50(11): 1410-1416. DOI: 10.3969/j.issn.1001-5078.2020.11.020
HAO Jianxin, WANG Li. Infrared image segmentation of circuit board based on improved PCNN[J]. Laser & Infrared, 2020, 50(11): 1410-1416. DOI: 10.3969/j.issn.1001-5078.2020.11.020
|
| [7] |
徐奇伟, 黄宏, 张雪锋, 等. 基于改进区域全卷积网络的高压引线接头红外图像特征分析的在线故障诊断方法[J]. 电工技术学报, 2021, 36(7): 1380-1388.
XU Qiwei, HUANG Hong, ZHANG Xuefeng, et al. Online fault diagnosis method for infrared image feature analysis of high-voltage lead connectors based on improved R-FCN[J]. Transactions of China Electrotechnical Society, 2021, 36(7): 1380-1388.
|
| [8] |
袁刚, 许志浩, 康兵, 等. 基于DeepLabv3+网络的电流互感器红外图像分割方法[J]. 红外技术, 2021, 43(11): 1127-1134. http://hwjs.nvir.cn/article/id/b9df2f53-2244-471b-b0ec-42159cfaa654
YUAN Gang, XU Zhihao, KANG Bing, et al. DeepLabv3+ network-based infrared image segmentation method for current transformer[J]. Infrared Technology, 2021, 43(11): 1127-1134. http://hwjs.nvir.cn/article/id/b9df2f53-2244-471b-b0ec-42159cfaa654
|
| [9] |
Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative Adversarial Nets[M]. MIT Press, 2014.
|
| [10] |
Ronneberger O, Fischer P, Brox T. U-Net: Convolutional networks for biomedical image segmentation[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer International Publishing, 2015, DOI: 10.1007/978-3-319-24574-4_28.
|
| [11] |
ZHAO H, SHI J, QI X, et al. Pyramid scene parsing network[C]//IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017: 6230-6239.
|
| [12] |
胡智翔, 鲍胜利, 徐传淇, 等. 基于DeepLabv3+的遥感建筑物语义分割算法[J]. 计算机应用, 2021, 41(S2): 71-75.
HU Zhixiang, BAO Shengli, XU Chuanqi, et al. Semantic segmentation algorithm for remote sensing buildings based on DeepLabv3+[J]. Journal of Computer Applications, 2021, 41(S2): 71-75
|
| [1] | LIAO Guangfeng, GUAN Zhiwei, CHEN Qiang. An Improved Dual Discriminator Generative Adversarial Network Algorithm for Infrared and Visible Image Fusion[J]. Infrared Technology , 2025, 47(3): 367-375. |
| [2] | XUE Binlei, LAN Feng, ZHANG Shengxi, ZHANG Chunhui, LI Xiaofan. Terahertz Tomography of Substation Grounding Grid Fault based on Improved Generative Adversarial Networks[J]. Infrared Technology , 2025, 47(2): 257-263. |
| [3] | YUAN Hongchun, ZHANG Bo, CHENG Xin. Underwater Image Enhancement Algorithm Combining Transformer and Generative Adversarial Network[J]. Infrared Technology , 2024, 46(9): 975-983. |
| [4] | LI Li, YI Shi, LIU Xi, CHENG Xinghao, WANG Cheng. Infrared Image Deblurring Based on Dense Residual Generation Adversarial Network[J]. Infrared Technology , 2024, 46(6): 663-671. |
| [5] | WANG Tianyuan, LUO Xiaoqing, ZHANG Zhancheng. Infrared and Visible Image Fusion Based on Self-attention Learning[J]. Infrared Technology , 2023, 45(2): 171-177. |
| [6] | LIU He, ZHAO Tiancheng, LIU Junbo, JIAO Lixin, XU Zhihao, YUAN Xiaocui. Deep Residual UNet Network-based Infrared Image Segmentation Method for Electrical Equipment[J]. Infrared Technology , 2022, 44(12): 1351-1357. |
| [7] | WU Yuanyuan, WANG Zhishe, WANG Junyao, SHAO Wenyu, CHEN Yanlin. Infrared and Visible Image Fusion Using Attention- Based Generative Adversarial Networks[J]. Infrared Technology , 2022, 44(2): 170-178. |
| [8] | HUANG Mengtao, GAO Na, LIU Bao. Image Deblurring Method Based on a Dual-Discriminator Weighted Generative Adversarial Network[J]. Infrared Technology , 2022, 44(1): 41-46. |
| [9] | LUO Di, WANG Congqing, ZHOU Yongjun. A Visible and Infrared Image Fusion Method based on Generative Adversarial Networks and Attention Mechanism[J]. Infrared Technology , 2021, 43(6): 566-574. |
| [10] | ZHANG Pengcheng, HE Mingxia, CHEN Shuo, ZHANG Hongzhen, ZHANG Xinxin. Terahertz Image Enhancement Based on Generative Adversarial Network[J]. Infrared Technology , 2021, 43(4): 391-396. |
Supported by: Beijing Renhe Information Technology Co., Ltd. 
DownLoad: