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 use of mussel‑inspired polydopamine interlayer for high‑efficiency surface functionalization of PET fabrics

The surface modifications of polymer materials are carried out to improve surface properties, add new functionalities and thus enlarge their application areas. Polyethylene terephthalate (PET) is a commonly used textile fabric to achieve functional properties via surface modification techniques. However, its inert and non-reactive nature necessitates an activation process before the surface modification to create functional surfaces. Plasma treatment and chemical methods are commonly used for this aim. However, these techniques can easily damage the surface of the PET fabric and result in decreased mechanical properties. In this study, we proposed a new method to activate the surface of PET using polydopamine (PDA) interlayer, known as substrate-independent coating material, to form a better and more homogenous polyaniline (PAni) coating via an in-situ polymerization technique. The surface appearance of the samples was investigated using scanning electron microscopy, and the distribution of elements was analyzed using an energy-dispersive (EDS) detector. Thermal properties of the samples were explored using thermogravimetric analyses and Fourier-transform infrared spectroscopy was used to compare the chemical structures of the coated and uncoated samples. It was found that the PDA interlayer between PAni and PET significantly reduced the sheet resistance by providing more homogenous and chemically stable PAni coatings. Moreover, the effect of the PDA and PAni coating on the optical properties was investigated, and it was found that the PDA + PAni coated fabric exhibited a maximum of 10% reflectance in the range of 400 and 700 nm while uncoated fabric showed over 90%.

Source: Journal of Polymer Research
Publisher: Springer
Original Language: English
Document type: Article / Open Access

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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.

Source: Tekstil ve Konfeksiyon
Publisher: Ege University Textile and Apparel Research & Application Center
Original Language: English
Document type: Article / Open Access

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The Usage of Image Processing Techniques on the Determination of Pilling Grades

This compilation presents a detailed review of current research, developments, and progress on nanotechnology usage for the elimination of dyes from effluents released by textile industries. The benefits of using nanomaterials for functionalized textile production are presented, and the applications of nanomaterials in the most known functional technical textiles are discussed. The authors present the results of empirical studies carried out in the Portuguese industrial context, including the textile sector, where the relationship between negative effects associated with shift work and the adoption of certain management practices by organizations is analyzed. Additionally, the authors discuss how, to achieve the Fourth Industrial Revolution, technological tools must be incorporated into both the production and consumption of textiles. The closing study indicates that it is possible to make objective pilling detection easily for standard fabric structures in the textile industry using databases created by measuring lots of samples.

Chapter 5. The Usage of Image Processing Techniques on the Determination of Pilling Grades (Abdurrahman Telli, Department of Textile Engineering, Cukurova University, Adana, Turkey)

ABSTRACT: Pilling is a serious defect of fabric surface that gives an unpleasant appearance to garment. Pilling tendency is tested with different methods and devices in the laboratory conditions. The determination of the pilling grades is made with visual control by operators. Therefore, the human factor is significantly effective in this subjective evaluation method and may cause incorrect results. Studies in recent years show that objective methods based on image processing are preparing to replace subjective pilling assessments. In this chapter, difficulties in the subjective evaluation of the pilling grades were explained. Potential opportunities presented by image processing studies in the literature on the objective evaluation of the pilling grades were investigated. Image processing steps were given with various examples by using Image Processing Toolbox and codes in MATLAB software. In this study, it was indicated that it is possible to make an objective pilling detection easily for the fabric structures used as standard in the textile industry thanks to the databases to be created with measuring lots of samples.

ISBN: 978-1-53618-770-0

Publication Date: October 30, 2020

Original Language: English

Document type: Book/ Restricted Access

Publisher: Nova Science

Link: https://novapublishers.com/shop/challenges-and-opportunities-in-the-textile-industry/

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