基于GAN-SUNet网络的电路板红外图像分割方法  

Infrared Image Segmentation Method of Circuit Board Based on GAN-SUNet

作　　者：王力 夏璇 WANG Li;XIA Xuan(Airborne Electronic Systems Deep Maintenance Laboratory,College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学电子信息与自动化学院机载电子系统深度维修实验室,天津300300

出　　处：《红外技术》2025年第4期493-500,共8页Infrared Technology

基　　金：国家自然科学基金委员会与中国民用航空局联合资助基金(U1733119);中央高校基本业务费项目(3122017107)。

摘　　要：红外图像可以直观反映电路板温度及其变化情况。为了解决电路板红外图像上芯片定位困难的问题,本文提出了一种基于GAN-SUNet网络的电路板红外图像分割方法。SUNet网络是在UNet网络的基础上进行改进,通过引入空间金字塔池化模块(SPP)并修改网络损失函数,减少卷积核数量的方法提高网络检测精度和运行速度。首先,使用生成对抗网络(GAN)对采集到的电路板红外数据进行学习训练并生成仿真红外图像,扩充数据集;然后,使用生成的数据集对SUNet网络进行训练并通过调整模型参数提升其验证精度;最后,使用训练完毕的模型对电路板上的芯片进行识别检测与图像分割实现电路板红外图像芯片定位。实验结果表明:对于电路板红外图像分割,GAN-SUNet网络平均交并比达到93.77%,可以有效减轻人工定位芯片提取数据的压力,为之后芯片温度数据处理提供有力保障。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.

关 键 词：电路板图像分割 深度学习 红外图像 UNet 生成对抗网络 

分 类 号：TN219[电子电信—物理电子学]