Pointer meter recognition method based on improved Hough transform

Na LI; Jun WANG; Xing-fa DONG; Shao-peng SHI

doi:10.37188/CJLCD.2020-0179

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Pointer meter recognition method based on improved Hough transform

Image Processing | 更新时间：2021-08-05

- Pointer meter recognition method based on improved Hough transform
- Chinese Journal of Liquid Crystals and Displays Vol. 36, Issue 8, Pages: 1196-1203(2021)
- 作者机构：
  
  1.苏州科技大学电子信息工程学院, 江苏苏州 215009
  2.中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
- 作者简介：
- 基金信息：
  
  Jiangsu Province Graduate Workstation Project(2017272)
- DOI：10.37188/CJLCD.2020-0179
  CLC： TP391.4
- Received：11 July 2020，
  
  Revised：09 January 2021，
  
  Published：2021-08
- 稿件说明：
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Na LI, Jun WANG, Xing-fa DONG, et al. Pointer meter recognition method based on improved Hough transform[J]. Chinese journal of liquid crystals and displays, 2021, 36(8): 1196-1203.
DOI：

Na LI, Jun WANG, Xing-fa DONG, et al. Pointer meter recognition method based on improved Hough transform[J]. Chinese journal of liquid crystals and displays, 2021, 36(8): 1196-1203. DOI： 10.37188/CJLCD.2020-0179.

摘要

为解决指针式仪表自动识别系统中，光照不均匀、精确度不高等问题，提出一种Otsu算法和改进的Hough算法对仪表图像进行处理。首先预处理仪表图像，增强仪表指针区域特征，Otsu算法进行图像二值化，分割出仅属于指针的像素；再进行改进的Hough变换检测指针，通过快速提取表盘指针连通区域的中心像素点，结合表盘圆心约束，对提取过的像素点进行双阈值Hough变换直线检测。实验结果表明，提出的算法识别仪表读数最大相对误差为4.76%左右，满足系统精确度要求。

Abstract

In order to solve the problems of uneven illumination and low accuracy in the automatic recognition system of pointer instruments

an Otsu algorithm and an improved Hough algorithm are proposed to process the instrument image. Firstly

the instrument image is preprocessed to enhance the characteristics of the instrument pointer area

Otsu algorithm performs the image binarization to segment pixels that only belong to the pointer

and the improved Hough transform is performed to detect the pointer. By quickly extracting the center pixel point of the dial pointer's connected area

combined with the dial center constraint

the double threshold Hough is performed on the extracted pixel point transform straight line detection. Experimental results show that the proposed algorithm detects the meter reading error at about 4.76%

which meets the system accuracy requirements.

关键词

Keywords

references

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Related Author

Shao-peng SHI

Xing-fa DONG

Jun WANG

Na LI

Han-qing ZHAO

Xin QIAO

Guan-mao ZHANG

Jun-hong SUO

Related Institution

School of Electronic and Information Engineering， Suzhou University of Science and Technology

Chinese Academy of Science， Changchun Institute of Optics，Fine Mechanics and Physics

Institute of Optoelectronics and Electromagnetic Information, School of Information Science and Engineering, Lanzhou University

Key Laboratory of Airborne Optical Imaging and Measurement, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Graduate University of Chinese Academy of Sciences

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