Analysis of AFM images of Nanofibre Mats for Automated Processing - Tomasz Blachowicz (Tekstilec, 2020)
The image processing of pictures from fibres and fibrous materials facilitates the investigation of diverse geometrical properties, such as yarn hairiness, fibre bifurcations or fibre 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’s position. Previous investigations have proven the appropriateness of this method for examinations of different fibres, yarns and textile fabrics. In a recent study, we used AFM (atomic force microscopy) images, split into different greyscales, to analyse and quantify differences between various nanofibre mats created from polyacrylonitrile. In addition to the strong influence of the nanofibre diameters, a certain impact of the AFM settings was also seen and must be taken into account in future research.