吉林大学学报(信息科学版)

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工业线性指针仪表识别改进方法

霍凤财1a,1b,王迪1a,李政璋2   

  1. 1. 东北石油大学a. 电气信息工程学院; b. 黑龙江省网络化与智能控制重点实验室,黑龙江大庆163318;2. 大庆油田第九采油厂电力维修大队,黑龙江大庆163511
  • 收稿日期:2018-01-16 出版日期:2018-07-24
  • 作者简介:霍凤财( 1976— ) ,男,黑龙江安达人,东北石油大学副教授,博士,硕士生导师,主要从事智能算法和图像处理等研究,( Tel) 86-13936895698( E-mail) huofc@126. com。
  • 基金资助:
    国家自然科学基金资助项目( 61374127; 51404073) ; 国家自然科学基金优秀青年科学基金资助项目( 61422301) ; 中国博士后科学基金资助项目( 2014M550180) ; 黑龙江省教育厅科学技术研究基金资助项目( 12541090) ; 东北石油大学青年基金资助项目( 2013NQ105) ; 黑龙江省杰出青年科学基金资助项目( JC2015016)

Improved Recognition Method of Industrial Linear Pointer Meter

HUO Fengcai1a,1 b,WANG Di1a,LI Zhengzhang2   

  1. 1a. School of Electrical Engineering and Information; 1b. Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control,Northeast Petroleum University,Daqing 163318,China;2. No. 9 Production Plant Power Maintenance Team,Pettochina Daqing Oilfield,Daqing 163511,China
  • Received:2018-01-16 Online:2018-07-24

摘要: 为解决工业现场指针式仪表识别工作量繁重,人为误差较大的问题,提出了一种运用透视变换与Hough变换相结合的工业线性指针式仪表识别的方法。通过对采集的图像进行去噪、透视变换后,利用Hough 变换检测仪表指针的图像特征,并以该图像特征模拟出实际指针的偏转角度,利用该角度值计算最终读数,完成对工
业线性指针式仪表的识别工作。该方法在面临工业现场无法良好采集正视图像时,通过一定技术手段准确地识别出工业线性指针式仪表图像的读数。为新形势下,人工智能在工业现场的实际应用提供了一种新思路。

关键词: 计算机视觉, 图像滤波, Hough 变换, 透视变换

Abstract: In order to solve the problem of heavy workload and human error in industrial field pointer instrument identification,a method of industrial linear pointer instrument identification combined perspective transformation with Hough transform is proposed. After the image denoising and perspective transformation,Hough transform is used to detect the image features of the instrument pointer,and the actual pointer deflection angle is simulated with this image feature. Finally,the final number is calculated by this angle value,linear pointer instrument identification work is completed. When the frontal image cannot be well acquired in the field,recognizing industrial linear pointer meter readings is achieved well on some ways. In the new situation,a new way of thinking for the application of artificial intelligence in the industrial field is provided by this method.

Key words: image filtering, Hough transform, perspective transformation, computer vision

中图分类号: 

  • TP18