research-article

Automatic Identification Method of Pointer Meter under Complex Environment

Authors:

Liu Jiale,

Wu Huaiyu,

Chen ZhihuanAuthors Info & Claims

ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and Computing

Pages 276 - 282

https://doi.org/10.1145/3383972.3384047

Published: 26 May 2020 Publication History

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Abstract

As for the industrial pointer meter's recognition reading in outdoor scenes is easily affected by interference from complex environments such as light, occlusion, and blurred images, this article combines the theory and algorithm of case segmentation with pointer type in complex environments In meter detection and recognition, an automatic image segmentation and reading system for meter images was designed based on pyqt5. In the method designed in this paper, the de-noised image is firstly pre-processed by Non-Local Dehazing, Criminisi, and Deep Denoiseing Super Resolution, and then the instance segmentation algorithm Mask RCNN is used to segment and locate the pointer, and finally use the angle method for reading operation. Experimental tests show that this method can effectively overcome the interference of the complex environment on the pointer meter recognition, reduce the reading error, and has strong robustness and adaptive ability.

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Cited By

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Chen SCao JLi JGuo MXiang W(2024)Automatic Reading Method for Multi-Class Pointer Meters in Power Applications2024 43rd Chinese Control Conference (CCC)10.23919/CCC63176.2024.10662416(7961-7966)Online publication date: 28-Jul-2024
https://doi.org/10.23919/CCC63176.2024.10662416
Puchakayala SRavikumar AK V(2024)An ensemble deep learning model based high precision automated analog meter reading utilizing EfficientDet detection and U-Net segmentation2024 IEEE 3rd World Conference on Applied Intelligence and Computing (AIC)10.1109/AIC61668.2024.10730859(789-794)Online publication date: 27-Jul-2024
https://doi.org/10.1109/AIC61668.2024.10730859
Li JZhang HJia HShi DWang XZhang D(2023) Pointer-Type Instrument Recognition Based on Improved U 2 -net 2023 35th Chinese Control and Decision Conference (CCDC)10.1109/CCDC58219.2023.10326509(906-911)Online publication date: 20-May-2023
https://doi.org/10.1109/CCDC58219.2023.10326509

Index Terms

Automatic Identification Method of Pointer Meter under Complex Environment
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and Computing

February 2020

607 pages

ISBN:9781450376426

DOI:10.1145/3383972

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

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Published: 26 May 2020

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ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing

February 15 - 17, 2020

Shenzhen, China

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Chen SCao JLi JGuo MXiang W(2024)Automatic Reading Method for Multi-Class Pointer Meters in Power Applications2024 43rd Chinese Control Conference (CCC)10.23919/CCC63176.2024.10662416(7961-7966)Online publication date: 28-Jul-2024
https://doi.org/10.23919/CCC63176.2024.10662416
Puchakayala SRavikumar AK V(2024)An ensemble deep learning model based high precision automated analog meter reading utilizing EfficientDet detection and U-Net segmentation2024 IEEE 3rd World Conference on Applied Intelligence and Computing (AIC)10.1109/AIC61668.2024.10730859(789-794)Online publication date: 27-Jul-2024
https://doi.org/10.1109/AIC61668.2024.10730859
Li JZhang HJia HShi DWang XZhang D(2023) Pointer-Type Instrument Recognition Based on Improved U 2 -net 2023 35th Chinese Control and Decision Conference (CCDC)10.1109/CCDC58219.2023.10326509(906-911)Online publication date: 20-May-2023
https://doi.org/10.1109/CCDC58219.2023.10326509

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Deep learning for multisensor image resolution enhancement

Convolutional neural networks for wavelet domain super resolution

Microscopic image super resolution using deep convolutional neural networks

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