基于平面镜成像的纱线条干三维合成校准方法

针对二维图像纱线条干均匀度检测存在信息缺失、纱线条干三维合成准确度不高等问题,在平面镜成像的三维检测系统基础上提出一种纱线条干三维合成校准方法。选用4种不同粗细的纯棉集聚纺纱线,用相机在一幅图像中采集各个纱线的多视角图像,分别用校准方法对xoz平面和xoy平面校准,再进行二值化、形态学开运算处理,得到清晰的纱线条干二值图像,根据平面镜成像系统几何关系合成纱线条干三维模型,计算纱线条干各截面上像素点个数及其变异系数,与Uster TESTER 5测得的二维直径及纱线二维直径CV值对比评价纱线条干建模精度。结果表明,三维模型纱线各截面像素点个数与二维直径相关系数在0.987以上,条干均匀度CV值与Uster法结果的极差在2.36 %以内,证明校准方法可行。

Calibration method of three-dimensional yarn evenness based on mirrored image

Aiming at the lack of information in yarn detection from two-dimensional image and at the low accuracy of three-dimensional (3-D) yarn evenness, a calibration method for 3-D yarn evenness based on mirrored image was proposed. Four types of compact cotton yarn with different thickness were selected, and the multi-view images of each yarn were collected in one image by a camera. The collected images were calibrated on the xoz plane and xoy plane, while binarization and morphological opening were carried out respectively to obtain clear binary image of yarn evenness. According to the geometric relationship of the mirror imaging system, the 3-D model of yarn was created, and the number and CV value of white dots on each cross section of yarn were calculated. The modeling accuracy of yarn was evaluated by comparing with the yarn diameter and CV value of yarn diameter experimentally measured by Uster TESTER 5. The results show that the correlation coefficient between the number of pixels in each section of the 3-D yarn model and the diameter is more than 0.987, and the difference of CV value between the proposed method in this research and that from Uster testing is less than 2.36%, which proves the feasibility of the calibration method.