摘要
为了解决巡检机器人仪表识别精度不高,场景适应实用性低,无法实时处理等问题,对比分析了国内外几种不同的仪表指针识别方法,综合各类方法的优劣性,提出一种区域分割的图像处理算法与深度学习目标检测算法相结合的方法,使得指针式仪表自动识别算法趋于稳定,对环境的适应性变强。使用YOLOv5目标检测算法进行表盘定位,通过图像平滑、颜色校正、彩色增强处理,减弱现场光线对目标区域定位的影响,然后利用区域分割的图像处理算法对指针区域和刻度线区域进行图像分割,获得指针的矩形旋转中心和刻度线的最大、最小角度,根据指针角度和量程计算仪表示数,通过图像预处理和HSV颜色空间变换等算法提升指针提取能力。现实场景测试解决了指针仪表因受到遮挡、模糊、红线警示条等影响而难以准确进行表盘定位和指针提取的问题。实验结果表明,该方法不仅检测精度高、速度快,而且实用性强,满足机器人巡检要求。
Aiming at the problems of low precision of instrument identification,low practicability of scene adaptation,and inability of real-time processing of patrol robot,several different methods of meter pointer recognition at home and abroad are compared and analyzed.Based on the advantages and disadvantages of various methods,a method combining an image processing algorithm for region segmentation with a deep learning target detection algorithm is proposed to stabilize the automatic recognition algorithm for pointer instruments and enhance its adaptability to the environment.YOLOv5 target detection algorithm is used for dial positioning,image smoothing,color correction,and color enhancement processing are used to reduce the impact of on-site light on target area positioning.Then,the image processing algorithm for region segmentation is used to segment the pointer area and tick mark area,obtaining the maximum and minimum angles of the pointer's rectangular rotation center and tick mark.The instrument reading is calculated based on the pointer angle and range,the pointer extraction capability is improved through image pre-processing and HSV color space transformation algorithms.Based on real-scene testing,the problem of pointer instruments being affected by occlusion,blurriness,and red line warning bars,which makes it difficult to accurately locate the dial and extract the pointer,has been resolved.The experimental results show that this method is not only high in detection accuracy and speed,but also practical,and meets the requirements of robot patrol inspection.
作者
冯文奇
FENG Wenqi(Hebei Natural Gas Co.,Ltd.)
出处
《油气田地面工程》
2024年第3期7-13,共7页
Oil-Gas Field Surface Engineering
关键词
目标检测算法
区域分割
指针式仪表
仪表检测
object detection algorithm
area segmentation
pointer instrument
instrument detection
