Issue 1 / 2023
Special issue on Digital transformation
Inner covers
Article: Research on fabric classification based on graph neural network
Authors: PENG TAO, CAO WENLI, CHEN JIA, LV XINGHANG, ZHANG ZILI, LIU JUNPING, HU XINRONG
Pages: 3-11
DOI: 10.35530/IT.074.01.202224
Published online: February 2023
Abstract
Fabric classification plays a crucial role in the modern textile industry and fashion market. In the early stage, traditional
neural network methods were adopted to identify fabrics with the drawback of restricted fabric type and poor accuracy.
Combining multi-frame temporality and analysing fabric graph data made from fabric motion features, this paper
proposes a novel hybrid model that introduces the concept of graph networks to classify 30 textile materials in a public
database. We utilize the graph inductive representation learning method (GraphSAGE, Graph Sample and Aggregate)
to extract node embedding features of the fabric. Moreover, bidirectional gated recurrent unit and layer attention
mechanism (BiGRU-attention) are employed in the last layer of aggregation to calculate the score of previous cells.
Intending to further enhance performance, we link the jump connection with adaptive selection aggregation frameworks
to determine the influential region of each node. Our method breaks through the limitation that the original methods can
only classify a few fabrics with great classification results.
Keywords: fabric classification, multi-frame temporality, fabric graph data, GraphSAGE, BiGRU-attention
Citation: Tao, P., Wenli, C., Jia, C., Xinghang, L., Zili, Z., Junping, L., Xinrong, H., Research on fabric classification based on graph neural network, In: Industria Textila, 2023, 743, 1, 3–11, http://doi.org/10.35530/IT.074.01.202224
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Article: The restoration of garment heritages based on digital virtual technology: A case of the Chinese pale brown lace-encrusted unlined coat
Authors: HAN CHEN, HAN XU, YUDIAN ZHANG, WEIFAN WANG, ZHENGYANG LU
Pages 12-20
DOI: 10.35530/IT.074.01.202252
Published online: February 2023
Abstract
Garment heritages are commonly missing evidence of restoration because of their age and complex preservation
environment. Traditional restoration methods rely on the subjective experience of restoration personnel. Its restoration
results are difficult to achieve accuracy and objectivity, exposing precious cultural relics to the risk of irreversible
secondary damage. Taking the Pale Brown Lace-encrusted Unlined Coat as an example, this study puts forward a
method of garment heritages restoration based on digital virtual technology. After fully researching the garment
background information, we used deep learning and virtual twin technology to draw and cut the garment pieces, arrange
and sew the garments, and complete the stained patterns. The results show that our method can restore the original
appearance of the heritages relatively well, providing a new method reference for the inheritance and digital
transmission of traditional garment heritages.
Keywords: digitization, garment culture, deep learning, heritage restoration, pattern complement, virtual twin
Citation: Chen, H., Xu, H., Zhang, Y., Wang, W., Lu, Z., The restoration of garment heritages based on digital virtual technology: A case of the Chinese pale brown lace-encrusted unlined coat, In: Industria Textila, 2023, 74, 1, 12–20, http://doi.org/10.35530/IT.074.01.202252
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Article: Shaping the textile women’s digital work sustainability by legislative and taxation adjustments
Authors: BOSILJKA SREBRO, DRAGAN JANJUŠIĆ, VESNA MILETIĆ, DEJAN MILENKOVIĆ, GORAN DZAFIĆ, BORIS JEVTIĆ
Pages 21-27
DOI: 10.35530/IT.074.01.202262
Published online: February 2023
Abstract
The objective of this study is to examine the relationships between factors connected to the capability aspects of the
female working on the digital platform and the performance-sustainability of that employment. There are selected
3 groups of factors: first, professional learning and digital skills and capabilities of digital female workers; second,
entrepreneurial learning and orientation as a personal and corporate precondition for successful work online on a
platform, and third group of factors connected to the legal ecosystem issues, tax, social protection, and labour relations
as important frameworks to digital work sustainability. The dependent variable is defined as females from textile and
fashion design sub-sectors working online on the platform's sustainability, treated as performance. Empirical research
with 396 female participants working online on platforms connected to the jobs, tasks, and freelancing from textile,
fashion design, and other textile sub-sectors was provided in Serbia in 2022. They have by a five-level Likert scale
evaluated the level of the factors and their 16 statements' impact on the dependent variable. All three independent
variables do exhibit a positive relationship with the dependent one. The most significant influence has the professional
and digital skills and capabilities of female workers or their corporations. The paper’s findings can serve to remind female
digital workers that they cannot neglect the element of entrepreneurial capabilities and digital and professional skills in
their digital activities. The results can be useful for the government to enforce consistent, dynamic, and adjusted
taxation, social protection, incentives, and employment regulations for textile female digital workers and all others in
boosting employment within new flexible patterns and technologies. The research is further shown relative to the SDGs
on gender equality, digital divide issues, and pillars of social, economic, and environmental sustainability. The research
model for this study was drawn from the literature on digitalization, work flexibility, institutional, financial and social theory
and contributes to the current literature.
Keywords: female digital work, gender equality, gender digital divide, techno-entrepreneurship, textile and fashion
Citation: Srebro, B., Janjušić, D., Miletić, V., Milenković, D., Dzafić, G., Jevtić, B., Shaping the textile women’s digital work sustainability by legislative and taxation adjustments, In: Industria Textila, 2023, 74, 1, 21–27, http://doi.org/10.35530/IT.074.01.202262
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Article: Digital methods in the development of adaptive clothing for people with disabilities
Authors: MARCELA IROVAN, LILIANA INDRIE, VALENTINA FRUNZE, ELENA FLOREA-BURDUJA, ALIONA RARU
Pages 28–34
DOI: 10.35530/IT.074.01.202295
Published online: February 2023
Abstract
Social integration of people with disabilities is a significant issue, therefore effective interventions to provide
improvement of quality of life for people who have some kinds of disabilities are crucial. Specialists from various fields,
including those in the field of clothing design, are working on creating products that meet people with disabilities’ needs.
These products must be ergonomic, comfortable and provide the necessary psychological comfort. The whole process
of designing functional products is very complex, it requires continuous research, using knowledge from various fields
for better development of products.
This paper addresses the topic of developing adaptive clothing for people with multiple sclerosis in the context of social
inclusion and adaptation to new ways of life. All the proposals and ideas are analysed accordingly and different
constructive and technological solutions are proposed to customize and adapt the basic clothing.
Keywords: adaptive clothes, multiple sclerosis, 3D design, CLO 3D software, simulation
Citation: Irovan, M., Indrie, L., Frunze, V., Florea-Burduja, E., Raru, A., Digital methods in the development of adaptive clothing for people with disabilities, In: Industria Textila, 2023, 74, 1, 28–34, http://doi.org/10.35530/IT.074.01.202295
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Article: An undamaged pattern generation method from 3D scanned garment sample based on finite element approach
Authors: JIA-ZHEN CHEN, ZI-YI GUO, TAO LI, LEI DU, FENG-YUAN ZOU
Pages 35–41
DOI: 10.35530/IT.074.01.202185
Published online: February 2023
Abstract
The purpose of this study is to propose a new method to achieve pattern generation from garment sample without
damage. The non-contact three-dimensional (3D) scanner was employed to get the point cloud data of garment
samples. The Bowyer-Watson algorithm was used to implement Delaunay triangulation for surface reconstruction. The
finite element (FE) approach was employed to achieve the consideration of the fabric properties in surface development.
The proposed method was demonstrated to effectively realize the pattern generation of 3D sample clothes with fabric
properties without damaging the garment samples, and to be suitable for different clothing styles and fabrics. Compared
with traditional methods, the proposed method has higher accuracy (2.21% higher on average) and better stability.
Keywords: 3D scanned garment, fabric properties, finite element, pattern generation
Citation: Chen, J.-Z., Guo, Z.-Y., Li, T., Du, L., Zou, F.-Y., An undamaged pattern generation method from 3D scanned garment sample based on finite element approach, In: Industria Textila, 2023, 74, 1, 35–41, http://doi.org/10.35530/IT.074.01.202185
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Article: 3D interactive design of wedding dress
Authors: YANBO JI, YING WANG, KAIXUAN LIU, MENGYUE HU, CHUN ZHU, ZHAO LÜ, XIAONING LI
Pages 42–48
DOI: 10.35530/IT.074.01.2021111
Published online: February 2023
Abstract
Based on the human torso point cloud, this paper proposes a method from the 3D design of the corset to the 2D pattern
expansion. The point cloud of the human body is obtained through 3D scanning. The human body model for research
is constructed, and the 3D basic style design of the corset is carried out, based on the same style and different structural
line design, and through the curved surface flattening platform to convert 3D into 2D patterns. The verification was made
through a virtual simulation platform and physical production methods. This study enriches the application prospect of
digital technology in clothing design. Our proposed solution provides a more intuitive wedding dress design method and
improves fit and comfort. It can significantly reduce the difficulty of wedding pattern-making and improve the efficiency
of wedding design. In addition, our proposed method is not only suitable for wedding dress design, but also other styles
of clothing design.
Keywords: interactive design, wedding dress, pattern-making, try-on, fashion design
Citation: Ji, Y., Wang, Y., Liu, K., Hu, M., Zhu, C., Lü, Z., Li, X., 3D interactive design of wedding dress, In: Industria Textila, 2023, 74, 1, 42–48, http://doi.org/10.35530/IT.074.01.2021111
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Article: Research on garment flat multi-component recognition based on Mask R-CNN
Authors: TAO LI, YE-XIN LYU, LING MA, YONG XIE, FENG-YUAN ZOU
Pages 49–56
DOI: 10.35530/IT.074.01.202199
Published online: February 2023
Abstract
The automatic recognition of garment flat information has been widely researched through computer vision. However,
the unapparent visual feature and low recognition accuracy pose serious challenges to the application. Herein, inspired
by multi-object instance segmentation, the method of mask region convolutional neural network (Mask R-CNN) for
garment flat multi-component is proposed in this paper. The steps include feature enhancement, attribute annotation,
feature extraction, and bounding box regression and recognition. First, the Laplacian was employed to enhance the
image feature, and the Polygon annotated component attributes to reduce the interaction interference. Next, the ResNet
was applied to realize identity mapping to characterize redundant information of components. Finally, the feature map
was entered into two branches to achieve bounding box regression and recognition. The results demonstrated that the
proposed method could realize multi-component recognition effectively. Compared with the unenhanced feature, the
mAP increased by 2.27%, reaching 97.87%, and the average F1 was 0.958. Compared to VGGNet and MobileNet, the
ResNet backbone used for Mask R-CNN could improve the mAP by 11.55%. Mask R-CNN was more robust than the
state-of-the-art methods and more suitable for garment flat multi-component recognition.
Keywords: Mask R-CNN, garment flat, feature enhancement, multi-component network, component localization and recognition
Citation: Li, T., Lyu, Y.-X., Ma, L., Xie, Y., Zou, F.-Y., Research on garment flat multi-component recognition based on Mask R -CNN, In: Industria Textila, 2023, 74, 1, 49–56, http://doi.org/10.35530/IT.074.01.202199
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Article: Determination of used textiles drape characteristics for circular economy
Authors: ZLATIN ZLATEV, LILIANA INDRIE, JULIETA ILIEVA, CRISTINA SECAN, SIMONA TRIPA
Pages 57–66
DOI: 10.35530/IT.074.01.202241
Published online: February 2023
Abstract
In the present work, the drape characteristics of second-hand textile fabrics were determined. The results can be used
to implement the concepts of the circular economy. Automated software tools have been adapted and researched to
apply the proposed methods and procedures for digital image analysis of used textile drape, which will be utilized to
describe their shapes and predict their characteristics, as well as their classification into groups and assessment of
classification accuracy in recognizing their elements. A radius-vector function was used to determine the main drape
characteristics, such as the number of peaks, their size, and their location. Analytical models have been created for
automated forecasting of the drape characteristics from used textiles, which can be applied to predict changes in these
characteristics. It obtained an accuracy of 68–92% in the prediction of the main drape characteristics of used textiles.
Due to changes in their main characteristics, the errors in classification and prediction increased by 10–15%. More
complex computational procedures have been implemented to obtain a higher predictive power for second-hand textile
fabrics. The results can be applied in the manufacture of new products such as curtains, tablecloths, napkins and fashion
accessories.
Keywords: used textile fabrics, drape coefficient, color digital images, regression analysis, fabric characteristics
Citation: Zlatev, Z., Indrie, L., Ilieva, J., Secan, C., Tripa, S., Determination of used textiles drape characteristics for circular economy, In: Industria Textila, 2023, 74, 1, 57–66, http://doi.org/10.35530/IT.074.01.202241
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Article: Non-contact clothing anthropometry based on two-dimensional image contour detection and feature point recognition
Authors: YUZHUO LI, LEI JIANG, XINRONG LI, WENQIAN FENG
Pages 67–73
DOI: 10.35530/IT.074.01.202279
Published online: February 2023
Abstract
Developing the technology of estimating human body size from two-dimensional images is the key to realising more
digitalization and artificial intelligence in the textile and garment industry. Therefore, this paper is an in-depth study of
estimating body sizes from two-dimensional images in a self-collected database of human body samples. First, the
artificial thresholds in the Canny edge operator were replaced by adaptive thresholds. The improved Canny edge
operator was combined with mathematical morphology so that it could detect a clear and complete single human
contour. Then a joint point detection algorithm based on a convolution neural network and human proportion is
proposed. It can detect human feature points with different body proportions. Finally, front and side images and manual
body measurements of 122 males aged 18–22 years were collected as the human sample database, calculating the
length and fit of the girth size. Compared with manual body measurement data, the error of human length and girth size
parameters within the national standard range of –1.5 ~ 1.5 cm can reach 91% on average. This study provides an
accurate and convenient anthropometric method for digital garment engineering, which can be used for online shopping
and garment customization, and has a certain practical value.
Keywords: anthropometry, textile clothing, image processing, contour detection, feature point detection
Citation: Li, Y., Jiang, L., Li, X., Feng, W., Non-contact clothing anthropometry based on two-dimensional image contour detection and feature point recognition, In: Industria Textila, 2023, 74, 1, 67–73, http://doi.org/10.35530/IT.074.01.202279
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Article: Pants design and pattern generation based on body images
Authors: SHOU-NING JIN, BING-FEI GU, BEI-BEI ZHANG, YUAN-PING XIA, HUA-ZHOU HE
Pages 74–80
DOI: 10.35530/IT.074.01.20223
Published online: February 2023
Abstract
The personalized pattern generation method based on 2D body-measuring technology has considerable application
potential in clothing e-commerce, remote clothing customization, clothing production, and other aspects. By inputting the
front and side body images, this study proposed a new method of generating personalized patterns automatically. The
silhouettes could be extracted from the body images to estimate body sizes and design style. The basic rules between
the patterns and the body sizes were analysed, and the rules of the general pattern generation were established through
a knowledge-based combination of the basic pattern and the style parameters. The sizes extracted from images were
compared with the manually measured values, and the errors of these sizes were analysed. Sample pants were made
and tried on with the automatic pattern generation system, and the experiments showed that the sample pants have a
good fit at some key landmarks. As a result, this system can automatically generate personalized patterns and style
designs based on 2D human body images, to improve garment fit and accelerate clothing customization.
Keywords: size extraction learning, silhouette design, prediction model, body-garment relationship
Citation: Jin, S.-N., Gu, B.-F., Zhang, B.-B., Xia, Y.-P., He, H.-Z., Pants design and pattern generation based on body images, In: Industria Textila, 2023, 74, 1, 74–80, http://doi.org/10.35530/IT.074.01.20223
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Article: Group consumers' preference recommendation algorithm model for online apparel's colour based on Kansei engineering
Authors: BAORU GE, NAZLINA SHAARI, MOHD YAZID MOHD YUNOS, SAZRINEE ZAINAL ABIDIN
Pages 81–89
DOI: 10.35530/IT.074.01.202268
Published online: February 2023
Abstract
The sales growth rate of men's plain-colour shirts dropped significantly online in China. Consumers first pay attention to
the appearance design of clothing online. It only takes 7 seconds for consumers to determine a product, and the colour
in its appearance design accounts for about 67% of the role. Thus, this study took the colour design of men's plain-colour
shirts as an example in China, established the basic colour calculation scale and an algorithm model of group
consumers' product preferences based on Kansei Engineering and scientific mathematics, to provide new sales ideas
and methods for retailers and markets online. Firstly, this study obtained the crucial Kansei word pairs (emotional
preferences) and colour design elements through interviews, literature, magazines and websites, word frequency
statistics, card sorting and cluster analysis. Then, researchers established a basic colour calculation scale of
cross-loading through Kansei Engineering and partial least squares (PLS). Finally, a recommendation set of products is
obtained using the analytic hierarchy process (AHP), the weight of Kansei word pairs, and the distance calculation of
comprehensive evaluation value based on consumers' emotional needs. That is, this study obtained consumers'
aesthetic emotional preference for men's plain-colour shirts in China, colour design elements of shirts that are widely
recognized and accepted, basic colour calculation scales, recommendation preferences algorithms and models for
group consumers, and verified their effectiveness by PCA.
Keywords: men's plain-colour shirts, Kansei engineering, algorithm model of recommendation, consumer's colour preference
Citation: Ge, B., Shaari, N., Yunos, M.Y.M., Abidin, S.Z., Group consumers' preference recommendation algorithm model for online apparel's colour based on Kansei engineering, In: Industria Textila, 2023, 74, 1, 81–89, http://doi.org/10.35530/IT.074.01.202268
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Article: Investments in digital technology advances in textiles
Authors: MARKO ŠPILER, DRAGAN MILOŠEVIĆ, MIROSLAV MIŠKIĆ, LADIN GOSTIMIROVIĆ, MILAN BESLAĆ, BORIS JEVTIĆ
Pages 90–97
DOI: 10.35530/IT.074.01.202287
Published online: February 2023
Abstract
The investments in digital technologies are expected to soon have a major impact on the textile and fashion companies’
sustainability and competitiveness. Motivated by these trends empirical research on investments of the fashion and
textile companies in ICT technologies-based advancement in the Serbian case was provided in 2022. Representatives
of 423 textile and fashion companies were asked about their investments in various digital technologies in the previous
three years and their digital transformation status. The research findings show that investments in cloud computing, IT,
energy management, automation, robotics, and machine learning technologies have a significant impact on the digital
transformation of companies. Most of them reached a medium level of transformation, fewer than a high level, with many
textile and fashion companies just defining digital transformation. The contribution of the research findings to the
investments in the companies’ digital transformation can be seen in the significance of the textile’s digital technology
implementation, which enables manufacturers and retailers to respond directly to market demand by reducing product
lead time and cost, increasing supply chain efficiency and profitability, and promising in terms of ensuring competitive
advantage in the risk and challenging business environment.
Keywords: artificial intelligence, cloud computing, digital technologies, innovation, textile and fashion industry, sustainability
Citation: Špiler, M., Milošević, D., Miškić, M., Gostimirović, L., Beslać, M., Jevtić, B., Investments in digital technology advances in textiles, In: Industria Textila, 2023, 74, 1, 90–97, http://doi.org/10.35530/IT.074.01.202287
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Article: The digital transformation of garment product development
Authors: MALINA ROSCA, ANA-DIANA VATRA, MANUELA AVADANEI
Pages 98–106
DOI: 10.35530/IT.074.01.2022148
Published online: February 2023
Abstract
Many clothing companies approach digital transformation by focusing on digitizing individual processes or operations.
Digital transformation is often limited to specific initiatives or programmes that only impact a few departments. Significant
opportunities or existential risks are often the main drivers for digital transformation. Moreover, leaders planning the
future of their companies and industries should focus on the opportunity – or existential threat – that these changes
present. It is essential to find the ideal balance between focusing on quick results with innovative ideas and laying the
foundation for digital transformation, such as unleashing the potential of data and analytics, managing brand and
reputational risk, controlling the entire supply chain and closing the digital technology gaps are not the only significant
issues. A complete change in corporate culture that puts the customer at the centre is the key component of the ultimate
digital challenge for clothing companies. This article presents the opportunities, benefits and challenges of developing
garment models with digital tools from Gemini CAD, a Lectra company. These tools include (in addition to the pattern)
the product data sheet, a detailed description of all fabrics, trimmings, and accessories, components needed for
sourcing, purchasing, and determining the cost of the product, as well as the information needed to publish the product
on e-commerce and interact with the customer, including customization.
Keywords: digital patterns, digital fabrics, trimmings, graphic resources
Citation: Rosca, M., Vatra, A.-D., Avadanei, M., The digital transformation of garment product development, In: Industria Textila, 2023, 74, 1, 98–106, http://doi.org/10.35530/IT.074.01.2022148
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Article: Digital solutions for bespoke apparel achieving mass customization in as service business models
Authors: IASMINA DIMCEA, DIANA CLAUDIA COZMIUC, DANIEL BOTEZ, DOINA DARVASI, MIRCEA UNTARU, RALF WAGNER, AUREL MIHAIL TITU
Pages 107–120
DOI: 10.35530/IT.074.01.202281
Published online: February 2023
Abstract
The Information and Communications Technology sector may be organized into individual technologies or solutions.
Theoretical literature review argues digitalization technologies make up enterprise architecture and shape business
processes or business models. It also shows contemporary business models market solutions for a given value or
impact, rather than sell individual technologies per se. Empirical data confirms enterprise architecture is the market for
system integration. Market data shows the market leader is Software AG. The goal of this article is to build a theory with
an emerging case example of more technologically and business model sophisticated solutions than the theoretical and
market benchmark. The methodology is a dual case study on important market players, Siemens and PTC. The
standalone cases allow for similar solutions which cannot be otherwise tested or validated. Reference is also paid to
other market players within the article. The empirical data analysis is compared to acceptable benchmarks, theoretical
literature review and the enterprise architecture market leader Software AG. Findings show emerging technologies add
capability maturity levels to accepted system integration. Network business models with a quantifiable and provable
customer value proposition: bespoke or personalized products, reasonable cost per item, and zero inventory achieve
the vision of mass customization. The business models are enabled by the highest level of digitalization capability
maturity, not considered in the status quo literature review and at the leading enterprise architect. They place the textile
industry at the forefront of technological innovation and extended reality-based marketing.
Keywords: bespoke products, enterprise architecture, platform business models, as a service business models
Citation: Dimcea, I., Cozmiuc, D.C., Botez, D., Darvasi, D., Untaru, M., Wagner, R., Titu, A.M., Digital solutions for bespoke apparel achieving mass customization in as service business models, In: Industria Textila, 2023, 74, 1, 107–120, http://doi.org/10.35530/IT.074.01.202281
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Article: Protective clothing system for interventions in emergency situations
Authors: DOINA TOMA, GEORGETA POPESCU, ALINA POPESCU, SABINA OLARU, ADRIAN SALISTEAN, IONELA BADEA
Pages 121–129
DOI: 10.35530/IT.074.01.1839
Published online: February 2023
Abstract
Emergency workers are exposed to many different risks at the same time and possible consequences for their safety
and health may be manifold. Many emergency workers suffer from accidents and injuries in the course of their jobs, as
well as other negative health effects that lead to severe deterioration of their physical and psychological well-being. The
use of specific personal protective equipment (PPE) according to the given risks is of great importance in preventing
adverse health effects among emergency workers. This research aimed to develop, for emergency workers, a PPE
system, in a modular structure consisting of: i) modular layer 1: the inner layer, in contact with the skin/Underwear PPE,
with the function of sensorial and thermophysiological comfort and which ensures thermal protection; ii) modular layer 2:
the intermediate (basic) layer/Duty uniform – with the function of limited protection to the specific risk factors of an
unpredictable intervention action (thermal risks: convection heat, flame; risks from the external environment: liquid
splashes; mechanical risks: cutting, abrasion, etc); iii) modular layer 3: the outer layer/specialized PPE, with a function
of barrier against specific risk factors for fire intervention missions, extreme weather conditions etc. This modular
approach provides some advantages, including preserving comfort and flexibility until the intervention mission requires
the use of the next level of protection. This helps ensure that emergency responders are not in the position of choosing
between their safety or mission effectiveness.
Keywords: protection, duty-uniform, mission-specific layers, modular layers, emergency workers
Citation: Toma, D., Popescu, G., Popescu, A., Olaru, S., Salistean, A., Badea, I., Protective clothing system for interventions in emergency situations, In: Industria Textila, 2023, 74, 1, 121–129, http://doi.org/10.35530/IT.074.01.1839
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