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Pointer Meter Recognition Method Based on Yolov7 and Hough Transform

Authors :
Chuanlei Zhang
Lei Shi
Dandan Zhang
Ting Ke
Jianrong Li
Source :
Applied Sciences, Vol 13, Iss 15, p 8722 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The current manual reading of substation pointer meters wastes human resources, and existing algorithms have limitations in accuracy and robustness for detecting various pointer meters. This paper proposes a method for recognizing pointer meters based on Yolov7 and Hough transform to improve their automatic readability. The proposed method consists of three main contributions: (1) Using Yolov7 object detection technology, which is the latest Yolo technology, to enhance instrument recognition accuracy. (2) Providing a formula for calculating the angle of a square pointer meter after Hough transformation. (3) Applying OCR recognition to the instrument dial to obtain the model and scale value. This information helps differentiate between meter models and determine the measuring range. Test results demonstrate that the proposed algorithm achieves high accuracy and robustness in detecting different types and ranges of instruments. The map of the Yolov7 model on the instrument dataset is as high as 99.8%. Additionally, the accuracy of pointer readings obtained using this method exceeds 95%, indicating promising applications for a wide range of scenarios.

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.598906660ca449c2b568981aa328eda6
Document Type :
article
Full Text :
https://doi.org/10.3390/app13158722