河南理工大学学报（自然科学版）2025，Vol.44Issue(5)：35-42,8.DOI:10.16186/j.cnki.1673-9787.2024070039
基于MobileNetV2的轻量级输电线路绝缘子图像分割方法
Lightweight image segmentation method for transmission line insulators based on MobileNetV2
摘要
Abstract
Objectives To address the issues of low accuracy in insulator segmentation in aerial images of transmission line inspections,limited computing power of edge devices,large model parameters,and insuf-ficient real-time performance,a lightweight transmission line insulator segmentation network(ISNet)based on MobileNetV2 was proposed.Methods Firstly,a lightweight MobileNetV2 was used as the encoder back-bone network to re extract multi-scale features from the input image;Secondly,a new diverse feature aggre-gation module(DFAM)was proposed,which aggregated diverse spatial position information and advanced semantic information through convolutional layers with different convolution kernels,channel attention,and spatial attention mechanisms;Finally,a multi-level symmetric decoder(MSD)was designed to fuse the output features from the same layer encoder and the previous decoder to generate the final prediction image.Results The experimental results showed that the proposed method achieved excellent performance on the aerial image insulator segmentation dataset.In terms of mIoU index,ISNet reached 90.9%,which was 5.2%and 1.2%higher than DeepLabV3plus and SegFormer,respectively;On the mPA metric,ISNet achieved 93.6%,which was 5.2%and 0.8%higher than DeepLabV3plus and SegFormer,respectively;In addition,the proposed method ISNet could achieve an inference speed of 71.2 F/s on a single NVIDIA RTX 3090 GPU,with only 3.1 M of parameters and 21.2 G of floating-point operations(FLOPs)(input im-age size of 1 024×1 024),which was superior to current mainstream semantic segmentation methods.Conclusions In summary,the proposed method ISNet achieved the best segmentation accuracy while im-proving the lightweighting and real-time performance of the model.关键词
MobileNetV2/语义分割/绝缘子/输电线路巡检/深度学习/计算机视觉Key words
MobileNetV2/semantic segmentation/insulator/transmission line inspection/deep learning/computer vision分类
信息技术与安全科学引用本文复制引用
孙世明,唐元合,邰曈,魏学云,方巍..基于MobileNetV2的轻量级输电线路绝缘子图像分割方法[J].河南理工大学学报（自然科学版）,2025,44(5):35-42,8.基金项目
国家自然科学基金资助项目(42475149) （42475149）
国电南瑞南京控制系统有限公司科技信息项目(2023h581) （2023h581）
