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A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection.

Zhu Li¹, Yisha Zhou¹, Qinghua Sheng¹

¹School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310000, China.

Sensors (Basel, Switzerland)

|October 24, 2020

Summary

This summary is machine-generated.

This study presents a novel algorithm for automatically reading pointer meters, improving accuracy and robustness. The method uses deep learning and polar transformation for reliable industrial meter measurement.

Keywords:

deep learning distance method pointer meter secondary search

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Area of Science:

Engineering
Computer Science
Metrology

Background:

Automatic reading of pointer meters is crucial for efficient industrial measurements.
Existing algorithms struggle with accuracy and robustness, particularly concerning illumination and shooting angles.
Variability in pointer meter designs presents a challenge for automated systems.

Purpose of the Study:

To develop a novel, adaptive algorithm for accurate and robust automatic reading of diverse pointer meters.
To overcome the limitations of existing methods in handling varying illumination and angles.
To enhance the efficiency and reliability of industrial meter measurements.

Main Methods:

Utilized deep learning for detecting and recognizing scale value text on meter dials.
Implemented image rectification and meter center determination based on text coordinates.
Employed polar transformation to convert circular scale regions into linear ones.
Determined pointer and scale line positions using a secondary search on an expanded graph.
Applied a distance method for reading the scale region indicated by the pointer.

Main Results:

The proposed algorithm demonstrated higher accuracy in detecting pointer meter readings.
The method exhibited improved robustness against variations in illumination and shooting angles.
Successful adaptive detection across different types of pointer meters was achieved.

Conclusions:

The novel algorithm offers a significant advancement in the automatic reading of pointer meters.
The approach provides a more accurate and robust solution compared to existing methods.
This technology has the potential to improve industrial meter measurement efficiency and reliability.