The image processing of pictures from fi bres and fi brous materials facilitates the investigation of diverse ge-ometrical properties, such as yarn hairiness, fi bre bifurcations or fi bre lengths and diameters. Such irregular sample sets are naturally suitable to the statistical examination of images, using a random-walk algorithm. This results in the calculation of the so-called Hurst exponent, which is the asymptotic scaling exponent of the mean squared displacement of the walker{\textquoteright}s position. Previous investigations have proven the appropri-ateness of this method for examinations of diff erent fi bres, yarns and textile fabrics. In a recent study, we used AFM (atomic force microscopy) images, split into diff erent greyscales, to analyse and quantify diff er-ences between various nanofi bre mats created from polyacrylonitrile. In addition to the strong infl uence of the nanofi bre diameters, a certain impact of the AFM settings was also seen and must be taken into account in future research.
\
\
}, year = {2020}, journal = {Tekstilec}, volume = {63}, chapter = {104}, month = {06/2020}, url = {http://www.tekstilec.si/wp-content/uploads/2020/06/10.14502Tekstilec2020.63.104-112.pdf}, doi = { DOI: 10.14502/Tekstilec2020.63.104-112}, language = {eng}, }