基于卷积神经网络的指针式仪表识别  

Recognition of Pointer Instrument Based on Convolution Neural Network

作　　者：李金红 熊继平[2] 陈泽辉 朱凌云[2] LI Jin-Hong;XIONG Ji-Ping;CHEN Ze-Hui;ZHU Ling-Yun(College of Mathematics and Computer Science,Zhejiang Normal University,Jinhua 321004,China;College of Physics and Electronic Information Engineering,Zhejiang Normal University,Jinhua 321004,China)

机构地区：[1]浙江师范大学数学与计算科学学院,金华321004 [2]浙江师范大学物理与电子信息工程学院,金华321004

出　　处：《计算机系统应用》2021年第9期85-91,共7页Computer Systems & Applications

摘　　要：目前大部分研究指针式仪表识别的方法中提取指针是完全基于传统的图像处理技术,提取过程较为复杂且步骤繁多.为了有效解决指针式仪表读数识别中指针中轴线所在直线提取困难及识别精度不高等问题,本文提出了一种基于深度学习的指针式仪表的识别方法.首先用Faster R-CNN算法检测仪表圆盘,再采用基于深度学习的方法Faster R-CNN算法检测指针,根据得到的指针目标框的位置信息裁剪得到指针图像,在指针图像的基础上进行二值化、细化、霍夫变换检测直线、最小二乘法拟合直线等步骤识别仪表最终读数.和直接在仪表表盘目标框图像或原始图像上进行传统图像处理相比很大程度上减少了定位指针中轴线所在直线过程中的干扰.实验结果表明本文所提出的基于深度学习的指针检测的平均准确率高达96.55%.对于复杂背景下指针式仪表的指针区域的检测具有良好的准确性与稳定性.At present,most of the pointer recognition methods are based on the traditional image processing technology,and the extraction process is complicated with many steps.To effectively solve the problems of difficult pointer axis extraction and poor reading recognition accuracy of a pointer instrument,this study introduces a method of pointer instrument recognition based on deep learning.First,the Faster R-CNN algorithm is used to detect the instrument disk,and then the method based on deep learning is adopted to detect the pointer.According to the position information of the target frame,the pointer image is obtained by clipping.The final reading of the instrument is identified by binarization,thinning,Hough transform,and the least square fitting line.Compared with the traditional image processing directly on the image of the panel target frame or the original image,this method greatly reduces the interference in the process of locating the line where the pointer axis is located.The experimental results show that the average accuracy of pointer detection based on deep learning proposed in this study is up to 96.55%.It has high accuracy and stability for pointer detection of the pointer instrument under a complex background.

关 键 词：深度学习 Faster R-CNN算法 指针检测 指针式仪表 读数识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP183[自动化与计算机技术—计算机科学与技术]