摘要
为了解决输电线路多金具检测任务中存在的小目标和密集遮挡问题并充分利用金具高分辨率航拍图像的信息优势,提出基于先验知识辅助聚类的粗-精输电线路多金具检测方法。首先,通过粗检测模块实现对输电线路高分辨率航拍图像的初步感知。接着,通过先验知识指导结构场景子区域选取模块中聚类算法半径的确定,以自适应聚类出合适的子区域。最后,设计精检测模块充分利用高分辨率航拍图像中的关键信息,进行金具的精确感知,并融合粗检测结果以实现由粗到精的金具识别。经实验证明,基于先验知识辅助聚类的粗-精输电线路多金具检测模型比之基线模型准确率提高了11.3%,对其中小目标金具和密集遮挡金具检测准确率的提高尤为明显。
To solve the problem of tiny-size objects and dense occlusion in the transmission line multi-fitting detection task and make full use of the information of fitting high-resolution aerial images,a coarse-fine transmission line multi-fitting detection method based on prior knowledge auxiliary clustering is proposed.First,the coarse detection module is utilized to realize the preliminary perception of the high-resolution aerial images of transmission lines.Then,the determination of clustering algorithm’s radius in structural scene sub-region selection module is guided through the prior knowledge for adaptively clustering the appropriate sub-regions.Finally,a fine detection module is designed to fully utilize key information from high-resolution aerial images for precise perception of fittings,and to realize the recognition of fittings from coarse to a finer level by fusing the coarse detection results.The experimental results show that the accuracy of the coarse-fine transmission line multi-fitting detection method based on prior knowledge auxiliary clustering is 11.3%higher than that of the baseline model.Especially,the detection accuracy of tiny-size fittings and dense occlusion fittings is improved obviously.
作者
翟永杰
郭聪彬
陈年昊
王璐瑶
王乾铭
赵文清
ZHAI Yongjie;GUO Congbin;CHEN Nianhao;WANG Luyao;WANG Qianming;ZHAO Wenqing(School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2024年第9期3742-3752,I0035,共12页
Proceedings of the CSEE
基金
国家自然科学基金项目(U21A20486)。
关键词
输电线路
金具
航拍图像
深度学习
目标检测
粗-精检测
transmission lines
fitting
aerial images
deep learning
object detection
coarse-fine detection
