筒子纱纱笼纱杆的定位检测方法  

Method for position detection of cheese yarn rod

作　　者：王文胜 李天剑[1] 冉宇辰 卢影 黄民[1] WANG Wensheng;LI Tianjian;RAN Yuchen;LU Ying;HUANG Min(Mechanical Electrical Engineering School, Beijing Information Science & Technology University, Beijing 100192, China;Beijing National Innovation Institute of Lightweight Ltd., Beijing 100083, China)

机构地区：[1]北京信息科技大学机电工程学院,北京100192 [2]北京机科国创轻量化科学研究院有限公司,北京100083

出　　处：《纺织学报》2020年第3期160-167,共8页Journal of Textile Research

基　　金：国家重点研发计划项目(2017YFB1304004);北京市教师队伍建设-创新团队(市级)项目(PXM2019_014224_000016);北京信息科技大学学校科研基金项目(1925003)。

摘　　要：为提高筒子纱纱笼纱杆偏移程度的自动化检测率,同时解决磨损缺陷纱杆自动定位检测准确率低的问题,提出了一种改进的频率调谐显著性检测算法进行筒子纱纱笼纱杆定位检测。首先,利用纱杆杆头金属面反光的特点和纱杆距离底面较远的特点,利用环形光源局部照射提高目标与背景对比度。然后利用目标位于图像中心附近的先验知识设计了分块加权模板进行改进频率调谐显著性检测算法,计算图像显著度。将显著图像使用最大类间方差法进行自动阈值分割后得到二值图像,并通过形态学滤波剔除明显不是目标的区域,最后通过霍夫变换圆拟合得到最终纱杆杆头位置坐标。现场实验和对比算法表明:改进方法具有抗缺陷能力,同时具有抗光照变化能力,可应用于工厂白天和晚上光线变化场景的任务。In order to improve the detection accuracy of cheese yarn packages and to reduce wear to the package rods,an improved frequency-tuned salient(FT)significance detection algorithm is proposed to detect the cheese yarn rod position.Firstly,making use of the characteristics of the metal surface reflection of yarn rods head and the farther distance of the yarn rods from the bottom surface,the local illumination of the ring light source was applied to improve the target and background contrast.Then,using a priori knowledge of the target located near the center of the image,a block weighting template was designed to improve the FT algorithm and calculate the image saliency.The maximum between-class variance method(OTSU)automatic threshold segmentation was performed on the salient image to obtain the binary image.Then,the region which was obviously not the target is removed by morphological filtration.Finally,the coordinates of the final yarn rods head position were obtained by Hough transform circular fitting.The field experiment and comparison algorithm show that the improved method has the ability to resist defects.In addition,it has the ability to resist light changes and can be applied to the daytime and nighttime lighting scenes of the factory.

关 键 词：机器视觉 筒子纱 定位检测 显著性检测 阈值分割 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论] TS190.4[自动化与计算机技术—计算机科学与技术]