The Impact and Importance of Fabric Image Preprocessing for the New Method of Individual Inter-Thread Pores Detection

Abstract

The paper describes the impact and importance of preprocessing methods of fabric image for detection of inter-thread pores (ITP), which is a new method of individual ITP identification. The aim of this experiment is to identify precisely every individual ITP of fabric structure by using optimal preprocessing algorithm for further quantitative, morphometric structural analysis of specialized fabrics (barriers, industrial filters, composites, others) in context of air permeability, flow resistance, UV radiation, viruses penetration, thermal comfort by estimation fabric porosity, especially macroporosity parameters and cover factor. The correct identification of individual ITP depends on the acquisition method and the preprocessing algorithm. It was conducted by analyzing the adaptation of digital image preprocessing methods for two structures of plain weave fabric in two magnification zooms, 1.25 and 0.8. Preprocessing operations were performed in the area of spatial operations of the image. The optimal preprocessing algorithm includes low-pass filtering, histogram equalization, nonlinear filtering, thresholding, and morphological operation. This algorithm was selected based on the factors developed by the author (ITP detection, RID factor—a difference between the real and model ITP areas) which rely on the ITP size, shape, and location. The graphic view of the ITP contour position on the fabric image is a verification element in the optimal preprocessing algorithm. The presented results of the air permeability of two different plain weave structures confirm the need to optimize the algorithm of pre-image processing methods to precisely detect each individual ITP in the fabric image.

Fusion of Cognitive Information: Evaluation and Evolution Method of Product Image Form

“…is also provides us with a new research idea in image cognition. Next, we will make a cognitive comparative study of color pictures and black and white pictures with preimage processing [51,52].…”

Advanced Image Analysis and Machine Learning Models for Accurate Cover Factor and Porosity Prediction in Knitted Fabrics: Tailored Applications in Sportswear, Swimwear, and Casual Wear

“…When conducting the image analysis, image processing is extremely important to reduce the loss of data on the structure and size of individual pores. Owczarek described the influence and importance of image pre-treatment methods for interstitial pore (ITP) detection with the aim of accurately identifying each ITP tissue structure using an opti-Fibers 2024, 12, 45 3 of 29 mal pre-treatment algorithm for further quantitative morphometric structural analysis of specialized fabrics [10]. As indicated, the main problem with ITP identification in image analysis was the misclassification of pixels that were close to the edges of the yarn, resulting in image noise among other problems.…”

Image-based analysis of single jersey loop parameters

“…Research on the automated determination of porosity has been demonstrated on knitted fabrics 17,18 and weaves. 19,20 Kostajnsek et al 20 give a detailed overview on methods used in the automated determination of porosity. On knitted fabrics, quality control is done by automated imaging in order to determine pilling 21 or do fabric error detection on circular knitting machines.…”

“…Research on the automated determination of porosity has been demonstrated on knitted fabrics 17,18 and weaves. 19,20 Kostajnsek et al. 20 give a detailed overview on methods used in the automated determination of porosity.…”