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.

中文翻译：

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一种使用光学相干断层扫描技术评估纺织品起球倾向的方法。

起球是由摩擦拉动和使材料的纤维起毛引起的。通常通过目测在平整织物表面上的药丸来评估起丸。在这里，我们基于光学相干断层扫描（OCT）图像中显示的织物的纹理特征，提出了一种起球评估的客观方法。首先在织物表面上方识别起球层。然后将伸出的纤维像素的百分比和Haralick的纹理特征用作起球描述符。主成分分析（PCA）用于选择高度相关的特征，然后降低特征空间的维数。第一个主成分用于量化织物起球的强度。实验研究结果证实，该方法可以确定起球强度。与传统的起球评估方法不同，它还可以在早期阶段检测起球。该方法可以帮助防止过高估计起球程度，从而避免不必要的程序，例如机械去除缠结的纤维。但是，这项研究仅涵盖了狭窄的一组织物，并且在检查了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的结论。