基于机器视觉的摄像整纬纬斜检测研究  

Research on Weft Skew Detection of Camera Weft Straightener Based on Machine Vision

作　　者：史先传[1] 许议元 殷帅 SHI Xianchuan;XU Yiyuan;YIN Shuai(College of Mechanical and Rail Transportation,Changzhou university,Changzhou 213164,China)

机构地区：[1]常州大学机械与轨道交通学院,江苏常州213164

出　　处：《计算机测量与控制》2023年第3期22-28,35,共8页Computer Measurement &Control

摘　　要：为了在线检测织物的纬纱倾斜量,研究了基于机器视觉的纬斜检测算法;首先采用改进后的陷波滤波器对织物图像进行频域滤波预处理,得到纬纱较为凸显的纹理图像描述;计算自相关图像初步提取纹理基元,随后构建大尺寸Sobel边缘检测模板,结合Blob分析提取纬纱纹理;再通过霍夫变换将纹理区域变换到参数空间,根据黑塞矩阵分析参数空间图像后,利用阈值逼近手段获取直线检测的阈值,最后反变换到图像空间中,显示出所有检测到的纬斜角;搭建摄像检测的硬件系统和软件界面,检测多类高密、低密织物,检测出的纬斜角度平均绝对误差小于0.35°,平均检测时间在225.5 ms内,能够满足整纬机的实际工作要求。In order to detect the skew value of fabrics online, a weft skew detection algorithm based on machine vision is studied. Firstly, for the sake of the more prominent weft yarn of the texture, an improved notch filter is used to preprocess the fabric image in frequency domain. Secondly, the autocorrelation image is calculated to initially extract texture primitives. Then, A large Sobel edge detection template is constructed to extract the weft texture with the Blob analysis. The texture domain is transformed into the parameter space by Hough transform, analyzing the parameter space image with Hessina Matrix is beneficial to obtain the threshold of line detection by the mean of threshold approximation. Finally, the transformation is reversed to display all detected weft skew angles. The camera detection hardware system and software interface are built to carry out the detection on both high density and low density fabrics. The results show that the mean absolute deviation is less than 0.35°and the average running time is less than 225.5 ms, which can meet the practical work application requirements of the weft straightener.

关 键 词：整纬系统 机器视觉 摄像检测 傅里叶变换 纹理提取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]