摘要
为解决水表示数自动识别问题,探索一种高效、准确的图像识别技术,以替代传统的人工读取方式。采用YOLOv7算法,结合图像处理技术,构建了一套自动化的水表示数识别系统。在水表公司内采集大量水表图片,以此为基础构建训练数据集。利用YOLOv7算法训练神经网络模型,实现对水表图像中关键元素(如水表字轮、整体水表及带指针的圆形分度盘)的精准检测。实验结果显示,该识别系统在识别水表字轮、水表整体及带指针圆形分度盘时的准确率(mPA@0.5)达到了97%,展现出卓越的性能。该系统不仅实现了快速检测,还确保了高准确率,显著提升了水表读数的效率与准确性。相较于传统的图像处理方法,基于YOLOv7算法的水表示数自动识别方法无需固定安装相机,对图像采集条件的要求更为宽松,因而具有更高的泛用性和实用性。该方法在水表等仪器仪表读数自动化领域具有重要的应用价值,有望推动相关行业的智能化进程。
To solve the problem of automatic recognition of water meter readings,an efficient and accurate image recognition technology is explored to replace the traditional manual reading methods.A set of automated water meter reading recognition system is constructed using YOLOv7 algorithm and image processing technology.Firstly,a large number of water meter images within the water meter company are collected to construct a training dataset.Subsequently,a neural network model is trained using the YOLOv7 algorithm to achieve accurate detection of key elements in the water meter image,such as the water meter wheel,the overall water meter,and the circular dial with pointers.The experimental results show that the recognition system has an accuracy rate(mPA@0.5)of 97% in identifying the water meter wheel,the water meter as a whole,and the circular dial with pointers,demonstrating excellent performance.This system not only achieves rapid detection,but also ensures high accuracy,significantly improving the efficiency and accuracy of water meter readings.Compared to traditional image processing methods,the automatic recognition method of water meter readings based on the YOLOv7 algorithm does not require a fixed camera installation and has the looser requirements for image acquisition conditions,thus having higher universality and practicality.This method has important application value in the field of automatic reading of water meters and other instruments,and is expected to promote the intelligent process of related industries.
作者
陈星瑜
娄嘉骏
江少锋
CHEN Xingyu;LOU Jiajun;JIANG Shaofeng(College of Testing and Optoelectronic Engineering,Nanchang Hangkong University,Nanchang 330063,China;Ningbo Water Meter(Group)Co.,Ltd.,Ningbo 315032,China)
出处
《仪表技术》
2024年第5期61-64,80,共5页
Instrumentation Technology
关键词
图像处理
目标检测
YOLOv7算法
聚类算法
image processing
object detection
YOLOv7 algorithms
clustering algorithms
