Porosity, the measure of the open spaces within a fabric structure, is a decisive factor in the performance of textiles. It influences breathability, permeability to liquids or gases, and suitability for various industries such as apparel, medical, and technical textiles. This study compares classical porosity calculation methods with non-destructive image analysis for 24 woven fabric samples that differ in density and weave pattern. Factors such as fabric density, weave pattern, illumination conditions, magnification, and the influence of the Otsu and Yen threshold algorithms were considered. The multifactor ANOVA statistical analysis shows that fabric density and weave pattern significantly influence porosity, with illumination playing an important role, while the threshold algorithm has a minor influence. A strong correlation is found between the actual fabric porosity and the results of the image analysis, except for double-sided illumination (reflective and transmissive), where the correlation is weakest. This comprehensive investigation provides valuable insights into the reliability of different porosity assessment approaches, which is essential for applications in various textile industries.
Keywords: image analysis; porosity; statistical analysis; woven fabrics.