The Evaluation of Uster Hairiness Results with an Image Analysis Approach

In this study, the images of the yarns were taken using a stereomicroscope. MATLAB software was used in image processing studies. The recommended image acquisition and processing steps in previous studies were followed, and the obtained results from textural parameters of images were compared with the results of Uster H and sh. The highest correlation in Uster H hairiness was obtained in the entropy textural parameter of the Sobel technique. The highest correlation in Uster sh hairiness was obtained in the mean of matrix elements (mean2) from the textural parameters in the Sobel technique. In general, higher correlation results were found in Uster sh than in Uster H. It has been observed that the Uster H results have deficiencies in determining the hairiness of dyed yarns. The different from the literature, this study presents that among the hairiness parameters, Uster sh shows the values closest to the real.

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Örme Kumaş Gözenekliliği ile Hava Geçirgenliği Arasındaki İlişkinin İncelenmesi

ÖZET: Bu çalışmada farklı yapı ve özellikte on iki adet 1x1 rib örme kumaş kullanılmıştır. Örme kumaşların hava geçirgenlikleri ölçülmüş ve mikroskop altında görüntüleri alınmıştır. Görsellerin MATLAB paket programında görüntü işleme teknikleriyle görüntü doku parametreleri analiz edilmiştir. Kumaş gözenekliliği ile ilgili sekiz farklı görüntü doku parametresi ve hava geçirgenliği arasındaki ilişki korelasyon analizi ile istatistiki olarak incelenmiştir. Aynı hammaddeden üretilmiş kumaşlarda kumaş gözenekliliği parametreleri ile hava geçirgenliği arasında güçlü bir ilişki bulunmuştur. Ancak farklı hammaddeler kullanıldığında bu güçlü ilişkinin azaldığı gözlenmiştir. Örme kumaşların hava geçirgenliği üzerinde iplik ve kumaş gözenekliliğine ek olarak lif özellikleri ve karışım oranının da etkileri tespit edilmiştir.

Investigation of the Relationship Between Porosity of Knitted Fabrics and Air Permeability

ABSTRACT: In this study, twelve 1x1 rib knitted fabrics containing different structure and features were used. Air permeability of knitted fabrics was measured and their images were taken under a microscope. Textural properties of images were analyzed with image processing techniques in MATLAB package program. The relationship between air permeability and eight different textural parameters of images related to fabric porosity were analyzed statistically with correlation analysis. A strong relationship was found between fabric porosity parameters and air permeability in fabrics produced from the same raw material. However, it was observed that this strong relationship decreased when different raw materials were preferred. The effects of fiber properties and blending ratio were determined on the air permeability of knitted fabrics in addition to yarn and fabric porosity.

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Opportunities Offered by Image Processing Technology in Textile and Apparel

Humans have always used their senses to assess the quality of products at the personal level or in the industry. For example, when buying fruit, people examine the fruit for the parameters they consider are important for assessing its quality such as colour, uniformity of colour, surface roughness, size, shape, surface defect. However, they are not able to assess internal damages or constituents of the fruit because their vision is limited to visible spectrum which is part of a vast electromagnetic spectra. Also, in industrial situations, assessment of objects can be affected by tiredness and fatigue of inspectors as well as different inspectors may assess the required quality parameters differently. Machine vision that involves collecting information from objects in visible or other spectra and analyzing the obtained information using image processing steps can assess the quality consistently over a long period as well as assess the internal and external quality parameters. With advances in high quality sensors (cameras) for different spectra, computing power of computers, and ease of developing software for a specific application, it has been possible to apply machine vision to many fields covered in this book.

Chapter 7- Opportunities Offered by Image Processing Technology in Textile and Apparel

Abdurrahman Telli

Department of Textile Engineering, Cukurova University, Adana, Turkey

ABSTRACT: Resolution, speed, and quality of image acquisition systems have made great advances in recent years. In addition to this, the development of the software industry offers significant opportunities in many areas. The textile and apparel sector is one of these areas. Image processing studies provide new techniques in textile characterization. In textile quality control, it can replace the subjective evaluations that can lead to wrong evaluation results due to people’s inexperience, fatigue, and differences in perspectives. Image processing offers objective evaluation opportunities. In fabric defect detection, it helps to find defects either online or offline that the human eye cannot perceive. It prevents material and time wastage and increases quality. With the processing of the images taken from body scanning devices, more accurate information is obtained for clothing patterns. Digital libraries have been created by processing fiber, yarn, and fabric images. Design programs that include all stages from the yarn to the image of the garment on the model have been started to be used. Image processing offers opportunities to eliminate the damages caused by the fast fashion trend. In this chapter, current and potential usage possibilities of image processing technology in textile and apparel fields are discussed.

ISBN: 979-8-88697-975-6

Publication Date: September 15, 2023

Original Language: English

Document type: Book/ Restricted Access

Publisher: Nova Science

Link: https://novapublishers.com/shop/image-processing-advances-in-applications-and-research/

 

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The Comparison of the Edge Detection Methods in the Determination of Yarn Hairiness through Image Processing

The resolution, quality and speed of the cameras have improved enormously in recent years. The combination of camera advancements and the software industry offers significant opportunities. 

In this study, an image processing approach for the determination of yarn hairiness was presented. Yarn images taken under a microscope were examined in MATLAB software. 

Seven different edge detection algorithms were used in order to separate the hairs from the yarn body. Seven different textural properties of obtained yarn images were compared with Zweigle hairiness test results. The findings have indicated that yarn hairiness can be clearly detected from microscope images with a six-step algorithm. 

The first four phases are grayscale, double format, 2D median filtering and histogram-fitting, respectively. The fifth stage is the edge detection algorithm and the sixth stage is the use of textural parameters. When compared with the Zweigle hairiness results, the most obvious finding to emerge from this study is that the best appropriate technique for edge detection was the Sobel method, and the textural parameter to be used in the evaluation was the standard deviation of matrix elements.

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Objective Measurement of Pilling Resistance in Knitted Fabrics with Image Processing Techniques

In the textile industry, measurement techniques based on image processing principles prepare to take over subjective evalution.

In this study, MATLAB software was used to evaluate pilling of knitted fabrics as objective. Knitted fabric images were taken in the cycles of 1000, 2000, 3000, 5000 and 7000.

Fabric’s surface digitization, pills detection and segmentation were carried out from these images.

Texture analysis was performed with Gray Level Co-occurrence Matrix (GLCM). After this phase, pill quantizations were made using images in matrix format obtained from image processing studies.

Standart deviation, entropy and mean of matrix elements, pill count, pill area and contrast values increased with the increase of rubbing cycles applied on the fabric.

Furthermore, the increase of rubbing cycles caused decrease in energy and homogeneity.

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