Institute of Applied Computer Science, Lodz University of Technology, 90-924 Lodz, Poland.
Institute of Electrical Engineering Systems, Lodz University of Technology, 90-924 Lodz, Poland.
Sensors (Basel). 2020 Jul 1;20(13):3687. doi: 10.3390/s20133687.
Pilling is caused by friction pulling and fuzzing the fibers of a material. Pilling is normally evaluated by visually counting the pills on a flat fabric surface. Here, we propose an objective method of pilling assessment, based on the textural characteristics of the fabric shown in optical coherence tomography (OCT) images. The pilling layer is first identified above the fabric surface. The percentage of protruding fiber pixels and Haralick's textural features are then used as pilling descriptors. Principal component analysis (PCA) is employed to select strongly correlated features and then reduce the feature space dimensionality. The first principal component is used to quantify the intensity of fabric pilling. The results of experimental studies confirm that this method can determine the intensity of pilling. Unlike traditional methods of pilling assessment, it can also detect pilling in its early stages. The approach could help to prevent overestimation of the degree of pilling, thereby avoiding unnecessary procedures, such as mechanical removal of entangled fibers. However, the research covered a narrow group of fabrics and wider conclusions about the usefulness and limitations of this method can be drawn after examining fabrics of different thickness and chemical composition of fibers.
起球是由摩擦拉扯和起绒纤维材料引起的。起球通常通过在平整的织物表面上目视计数来评估。在这里,我们提出了一种基于织物光学相干断层扫描(OCT)图像的纹理特征的客观起球评估方法。首先在织物表面上方识别起球层。然后,将突出纤维像素的百分比和 Haralick 纹理特征用作起球描述符。主成分分析(PCA)用于选择强相关特征,然后降低特征空间的维数。第一主成分用于量化织物起球的强度。实验研究的结果证实,该方法可以确定起球的强度。与传统的起球评估方法不同,它还可以检测到早期的起球。该方法有助于防止对起球程度的过高估计,从而避免不必要的程序,如机械去除纠缠的纤维。然而,该研究涵盖了一组较窄的织物,在研究不同厚度和纤维化学成分的织物后,可以得出关于该方法的有用性和局限性的更广泛结论。