An optimized design of the pointer meter image enhancement and automatic reading system in low illumination environment

被引：11

作者：

Ge, Wenqi ^{[1
]}

Yu, Xiaogang ^{[1
]}

Hu, Xiangyu ^{[2
]}

Wang, Xiaotong ^{[1
]}

机构：

[1] Tianjin Chengjian Univ, Sch Control & Mech Engn, Tianjin 300380, Peoples R China

[2] High Voltage Branch State Grid Tianjin Elect Power, Tianjin 300232, Peoples R China

来源：

MEASUREMENT SCIENCE AND TECHNOLOGY | 2023年 / 34卷 / 10期

基金：

美国国家科学基金会;

关键词：

low illumination environment; image enhancement; pointer meter; LSD algorithm; automatic reading; COMPUTER VISION; CALIBRATION; ALGORITHM; RETINEX;

D O I：

10.1088/1361-6501/ace3e8

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

As meter data becomes more and more important in the power industry, detection robots are led into substations for automatic collection of the pointer meters. However, the meter images captured in low illumination environments are unclear, resulting in poor recognition of the meter reading. A low-illumination image enhancement method based on virtual exposure is proposed in this paper, improving the dark and bright areas of low-illumination images, respectively. Then the image fusion was performed based on the Laplace pyramid to obtain clear meter images. In addition, the dial area was extracted using the Hough circle transform, and the pointer's rotation center was fitted using the least squares approach. Finally, the straight line of the pointer was extracted, and the data reading was based on the line segment detector algorithm. Case studies show the above method has good robustness in low illumination environment, with high rate, and accuracy during the image enhancement and automatic reading of the pointer meter.

引用

页数：11

共 30 条

[11] A multiscale retinex for bridging the gap between color images and the human observation of scenes [J].

Jobson, DJ ;

Rahman, ZU ;

Woodell, GA .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (07) :965-976

[12] Properties and performance of a center/surround retinex [J].

Jobson, DJ ;

Rahman, ZU ;

Woodell, GA .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (03) :451-462

[13] Image Contrast Enhancement Using Classified Virtual Exposure Image Fusion [J].

Lee, Chang-Hsing ;

Chen, Ling-Hwei ;

Wang, Wei-Kang .

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2012, 58 (04) :1253-1261

[14] Two projection methods for Regularized Total Least Squares approximation [J].

Lee, Geunseop ;

Barlow, Jesse L. .

LINEAR ALGEBRA AND ITS APPLICATIONS, 2014, 461 :18-41

[15] Remote Sensing Image Fusion Based on Sparse Representation and Guided Filtering [J].

Ma, Xiaole ;

Hu, Shaohai ;

Liu, Shuaiqi ;

Fang, Jing ;

Xu, Shuwen .

ELECTRONICS, 2019, 8 (03)

[16] A robust and high-precision automatic reading algorithm of pointer meters based on machine vision [J].

Ma, Yifan ;

Jiang, Qi .

MEASUREMENT SCIENCE AND TECHNOLOGY, 2019, 30 (01)

[17]

SABLATNIG R, 1994, INT C PATT RECOG, P794, DOI 10.1109/ICPR.1994.576447

[18] Image-based Automatic Dial Meter Reading in Unconstrained Scenarios [J].

Salomon G. ;

Laroca R. ;

Menotti D. .

Measurement: Journal of the International Measurement Confederation, 2022, 204

[19]

Thepade Sudeep D., 2020, 2020 IEEE Bombay Section Signature Conference (IBSSC), P69, DOI 10.1109/IBSSC51096.2020.9332217

[20] LSD: a Line Segment Detector [J].

von Gioi, Rafael Grompone ;

Jakubowicz, Jeremie ;

Morel, Jean-Michel ;

Randall, Gregory .

IMAGE PROCESSING ON LINE, 2012, 2 :35-55

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