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Automatic Recognition Reading Method of Pointer Meter Based on YOLOv5-MR Model.

Le Zou¹, Kai Wang¹, Xiaofeng Wang¹

¹School of Artificial Intelligence and Big Data, Hefei University, Heifei 230601, China.

Sensors (Basel, Switzerland)

|July 29, 2023

Summary

This summary is machine-generated.

This study introduces an improved YOLOv5-Meter Reading (YOLOv5-MR) model for accurate automatic meter reading. The enhanced model achieves higher precision in detecting pointer-type meters, reducing errors in intelligent inspection.

Keywords:

deep learning meter reading object detection substation patrol

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Area of Science:

Intelligent inspection systems
Computer vision applications
Metrology and instrumentation

Background:

Current automatic meter reading methods using target detection suffer from low accuracy and significant errors.
Pointer-type meters require precise visual interpretation for accurate readings.

Purpose of the Study:

To enhance the accuracy of automatic meter reading for pointer-type meters.
To develop an improved target detection model for meter reading applications.

Main Methods:

Proposed an automatic reading method based on the YOLOv5-Meter Reading (YOLOv5-MR) model.
Integrated a multi-scale target detection layer and designed custom Anchors for improved small target detection.
Optimized the loss function and up-sampling methods for faster model convergence.
Developed a novel external circle fitting method and employed a center angle algorithm for dial reading calculation.

Main Results:

The YOLOv5-MR model achieved a Mean Average Precision (mAP) of 79% on a self-built dataset.
Demonstrated a 3% improvement in mAP compared to the standard YOLOv5 model.
Outperformed existing advanced pointer-type meter reading models in experimental evaluations.

Conclusions:

The proposed YOLOv5-MR model significantly improves the accuracy of automatic meter reading for pointer-type meters.
The enhancements in target detection, model training, and reading calculation contribute to superior performance.
This method offers a more reliable solution for intelligent inspection tasks involving meter readings.