Evaluation of yarn appearance on a blackboard based on image processing
Evaluation of yarn appearance on a blackboard based on image processing
复制标题
基于图像处理的纱线黑板外观评价
DOI：
10.1177/00405175211002863
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发表时间：
2021-03-15
影响因子：
2.3
通讯作者：
Gao, Weidong
中科院分区：
文献类型：
--
作者：
Wang, Lei;Lu, Yichen;Gao, Weidong
纱线的条干和毛羽是纱线的外观特征，影响纺织加工和产品质量。为了经济有效地评价纱线外观，本文提出了一种分析黑板上纱线外观的图像处理方法。首先，扫描器捕获纱线黑板的图像。然后，利用图像处理算法对采集的图像进行纱线芯和毛状纤维的分割。根据图像中的纱芯信息和毛状纤维信息，分别计算出纱线直径变异系数CVbd和毛羽指数M。最后，将所提方法的结果与乌斯特测试仪的结果进行了比较。实验结果表明，利用纱线黑板图像可以客观地评价纱线的外观。同一纱线制成的不同纱线黑板的测试结果稳定一致。提出的方法与Uster Tester的相关系数为0.98，证明毛羽预测模型可以准确预测H值。用M值建立的毛羽预测模型对乌斯特测试仪的相应值进行预测，也证明了该模型的准确性。与现有的纱线条干和毛羽测试方法相比，该方法更加经济实用。
Yarn evenness and hairiness are the appearance characteristics of yarn, which affect textile processing and product quality. To evaluate yarn appearance economically and effectively, an image-processing method is proposed in this paper to analyze yarn appearance on a blackboard. Firstly, an image of a yarn blackboard is captured by the scanner. Then, the yarn core and hairy fibers are segmented from the captured image with image-processing algorithms. The coefficients of variation of the yarn diameter (CVbd) and the hairiness index (M) are respectively calculated based on the information about the yarn core and hairy fibers in the image. Finally, the results of the proposed method are compared with those from the Uster Tester. The experimental results demonstrate that yarn appearance can be objectively evaluated using yarn blackboard images. The test results of different yarn blackboards made from the same yarn are stable and consistent. The correlation coefficient between the proposed method and the Uster Tester is 0.98, which proves that the H value can be accurately predicted by the hairiness prediction model. A hairiness prediction model built by the M value is also proven to be accurate when used to predict the corresponding value of the Uster Tester. Compared with the existing yarn evenness and hairiness test methods, the proposed method is more economical and practical.