A Coarse-to-fine Meter Recognition Method in Substations
Authors: 
Zhenling Li, Futao Liu, Yuezhong Wan, Weida Cao, Fukui Wang, Xiaolei LiAuthors Info & Claims
Zhenling Li, Futao Liu, Yuezhong Wan, Weida Cao, Fukui Wang, Xiaolei LiAuthors Info & ClaimsAbstract
In substations, recognizing pointer-type meters is a highly challenging task, and the accuracy of recognition is crucial for intelligent analysis and processing of substations. However, the current recognition accuracy for irregular dials and small target pointers is a little low, and achieving automatic reading of multiple types of pointer-type meters is still a huge challenge. To address these issues, this paper proposes a substation meter recognition method based on YOLOv5. The method combines YOLOv5 with U-Net to extract important information such as pointers, scales, and digits through object detection and image segmentation, and employs the HigherHRNet network and perspective transformation to process images. Additionally, a reading calculation method based on long scale distance is proposed to accurately read the pointer-type meters. Experimental results demonstrate the high feasibility and accuracy of this method, effectively addressing the challenges of reading multiple types of pointer-type meters in substations.
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- A Coarse-to-fine Meter Recognition Method in Substations
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Published In
November 2023
237 pages
ISBN:9798400709272
DOI:10.1145/3638682
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 22 May 2024
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VSIP 2023
VSIP 2023: 2023 the 5th International Conference on Video, Signal and Image Processing
November 24 - 26, 2023
Harbin, China
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