This paper deals with the possibility of a fast and accurate assessment of the number, size, and distribution of pores in transparent woven fabrics based on light penetration. The procedure of analyzing the pore structure in the fabrics based on a digital image is presented in detail. Fabric pores are treated as image particles and analyzed with the Java-based image processing software ImageJ. The obtained data relate to the constructional parameters of the fabric that allow for further analysis, provide the possibility to compare structurally similar or different samples as well as double check the results generated by optical or other means. This paper describes work on plain and similar to plain weaves. The conducted analysis revealed several expected and some unexpected results. Among the former, we can list the range of pore sizes in the examined woven fabrics, the distribution of pores in regard to their similarity, and the effect of dents. Examples of the latter are the magnitude of the cumulative percentage of pores in regard to the weave and the degree to which they participate in the inter-yarn and inter-fiber pores.
Knowing the reflection, transmission, and absorption properties of the yarns from which the woven fabric is made, prediction of a fabric’s UV-protective properties is simple. Using the geometrical properties of monofilament yarns and fabrics, which were determined optically, and following the cover factor theory, we have determined the areas of fabrics covered with no yarns, only one yarn, and two yarns. From a special selected set of high-module polyethylene terephthalate (PET) monofilament materials (e.g., fabrics), we have elaborated a method for determining the reflection, transmission, and absorption of yarns. By first defining the differently covered areas of fabrics, we were able to use them in a mathematical model for calculating and predicting the UV-protective properties of the fabrics. The calculated and measured values of the UV-protective properties of the selected test fabrics were highly correlated, with a correlation coefficient >0.98.
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