联合单目深度估计的输电导线异物检测方法

doi:10.3778/j.issn.1002-8331.2407-0097

摘要/Abstract

摘要： 针对输电导线异物检测中常见的背景误检与异物漏检问题，提出一种联合单目深度估计的输电导线异物检测方法。设计一种多层次特征融合的单目深度估计网络（multi-level feature fusion depth estimation，MFFDepth），在编码器使用多层次特征融合模块整合多级特征中的语义信息，并在编码器与解码器之间的跳跃连接处引入坐标注意力模块，提高网络在复杂场景下的全局深度感知能力；利用深度估计网络预测出的深度图，通过深度值聚类得到前景图像和前景深度阈值；随后联合目标检测网络YOLOX和前景深度阈值，以排除背景误检框，同时联合语义分割网络DeepLabv3+和深度前景图像，以解决异物漏检测问题；融合两个联合检测模块的检测结果，提升整体检测性能。实验结果表明，所提出的异物检测方法准确率达到92.9%，召回率达到95.8%，相比于原始YOLOX算法准确率和召回率分别提升了1.4%和8.3%，能够更加有效地完成输电导线异物检测任务。

关键词: 单目深度估计, 异物目标检测, 语义分割, 无人机, 输电导线

Abstract: To address background false positives and object misses in detecting foreign objects on transmission lines, a method using monocular depth estimation is proposed. The multi?level feature fusion depth estimation network (MFFDepth) integrates semantic information from multiple feature levels within the encoder and introduces a coordinate attention module in the skip connections between the encoder and decoder, enhancing global depth perception in complex scenes. Based on the predicted depth map, depth value clustering is used to obtain the foreground image and foreground depth threshold. The YOLOX object detection network, combined with the foreground depth threshold, excludes background false positives. The DeepLabv3+ semantic segmentation network, combined with the depth foreground image, addresses the issue of foreign object detection omission. Finally, the results from these two combined detection modules are fused to improve overall detection performance. Experimental results show that the proposed method achieves an accuracy of 92.9% and a recall rate of 95.8%, which are improvements of 1.4% and 8.3%, respectively, compared to the original YOLOX algorithm, effectively enhancing the detection of foreign objects on transmission lines.

Key words: monocular depth estimation, foreign object detection, semantic segmentation, unamed aerial vechile (UAV, transmission lines

胡广怡, 韩军, 倪源松, 王文帅, 陈炣燏. 联合单目深度估计的输电导线异物检测方法[J]. 计算机工程与应用, 2025, 61(23): 305-315.

HU Guangyi, HAN Jun, NI Yuansong, WANG Wenshuai, CHEN Keyu. Method for Foreign Object Detection on Transmission Lines Using Monocular Depth Estimation[J]. Computer Engineering and Applications, 2025, 61(23): 305-315.

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