A Statistical Model for Analyzing Anthropometric Data and Developing Clothing Sizing Systems for Libyan School Children

A garment sizing system is essential for effective clothing design and production. A sizing system classifies a specific population into homogeneous subgroups based on some key dimensions. Persons of the same subgroup have the same body shape characteristics, and share the same garment size. Anthropometric data plays important role in creating clothing sizing system. The current work represents the sixth step towards the overall goal of developing the Libyan children’s clothing standards system based on physical measurements of the human body of Libyan schoolchildren. The objective of the current work is to study the physical measurements of students aged 6 to 17 years in the stages of primary, secondary. The body measurements of school children in Benghazi were collected and analyzed using simple statistics methods to understand the body ranges and current of student in all stages to develop the system sizing. The measurements were collected from previous projects. Some measurements were collected to complement a work of 90 (male and female) students between 6, 7 and 8 years old from a school in Benghazi. ANOVA test was used to determine differences between age groups.

The historical way of embroidery of traditional clothing

Purpose of the article. Trace the historical origins and genesis of embroidery decoration of traditional Ukrainian clothing and analyze the implementation of technological and technical innovations in the decoration of Ukrainian clothing. The methodology is based on the principles of historicism, art history analysis, scientific objectivity, and consistency in the study of the genesis of the decoration of the Ukrainian dress. Scientific novelty. The current state of embroidery decoration of traditional Ukrainian clothing is revealed and the issue of introducing innovative technologies in modern clothing design is raised. Conclusions. Based on the results of the study, we can conclude that modern decoration imitates the traditions of folk dress, including more and more the latest technologies. The unique experience of modern masters is analyzed and the ways of development in the direction of the art of embroidery decoration are determined. A variety of embroidery techniques with limitless skillful potential appear alongside machine embroidery works. Keywords: traditions, fashion designer, embroidery, creativity, innovation, education.

Research on optimization design of men's suit considering users' perception

PurposeThis paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on users perception image and users' preference.Design/methodology/approachIn this paper, men's suit is composed into multiple design features under the design elements. Using the orthogonal experiment method, 16 schemes of the representative suit are designed. Through perception evaluation experiment, users' perception images and preference degree of the samples are obtained. By partial least squares (PLS) analysis method, the models between users' perception image, suit design features and users' preference are built.FindingsThe interrelationship between the three is identified by establishing PLS models between users' perception image, suit design features and users' preference. According to the coefficients of the models, the optimization schemes of men's suits considering users' perception image and preference are proposed. Verification results show that the optimization schemes are significantly better than other schemes.Originality/valueThe results of this paper can be used for consumer demand-oriented clothing design and provide references and methods for converting consumer's perceived needs into clothing design features.

Parents' Determinants Buying Intent on Environmentally Friendly Children's Clothing

Fast-fashion products encourage parents to spend more on their children’s necessities. As a result, children’s clothing consumption is increasingly higher in a family due to child growth and change of needs. Due to the short lifespan of children’s clothes, the waste of clothing is increasing rapidly. This research aims to study the opinion of parents and the acceptance of children’s environmental-friendly clothing. The research examined parents’ buying patterns such as shopping frequency, disposal practices and the purchase of child clothing experience. This work has embraced the idea of eco-fashion design to examine the clothing needs of children and the knowledge of the parents. Hence, a quantitative analysis was applied to research among parents in January 2020 in Malaysia. This research contributes to academic results about parents’ decision-making on the children clothing subject. The findings showed that parents were aware of the idea of sustainable apparel; the cost, quality, design, and health issues were the most significant factors that influenced consumer’s decisions to purchase children’s clothing. Sustainable children’s clothing was preferred by parents as it had multiple benefits which impacted children’s health, preserves the environment as well as cost and time effective. For future research, further exploration relating to disposal and sustainable clothing design for children is suggested.

Application of Gabor Image Recognition Technology in Intelligent Clothing Design

Aiming at the complex problem of image recognition feature extraction, this paper proposes an intelligent clothing design model based on parallel Gabor image feature extraction algorithm. Based on the intelligent parallel mode, the algorithm decomposes and merges the calculation process of the image Gabor transformation, decomposes the entire image Gabor feature extraction calculation process into a parallel part and a nonparallel part, and accelerates the parallel part by using multiple cores. The calculation results are then combined to achieve the purpose of multicore parallel acceleration of the entire calculation process. Secondly, based on the consideration of improving the real-time performance of the intelligent clothing design system, combined with the existing multicore environment, this paper uses the intelligent model to design and implement the image parallel Gabor feature extraction algorithm and uses image processing and analysis technology to analyze the visual elements of traditional clothing and identify and quantify to form a relatively complete clothing visual element evaluation system, which provides a basis for large-scale collection and automated evaluation of clothing visual effects, as well as clothing trend tracking and prediction. Experiments show that the algorithm can effectively shorten the calculation time of Gabor image feature extraction and can obtain a good speedup in a multicore environment. At the same time, it combines with a multiscale intelligent clothing classification algorithm, on the basis of the VS2008 platform, combined with OpenCV 2.0, designed and implemented an intelligent clothing design system, and conducted experiments and system tests. The experimental results show that the algorithm given in this paper can accurately segment fabric defects from the background, which proves that the detection algorithm has a good detection effect. Simulation results show that the algorithm proposed in this paper can more accurately identify the state of clothing features, and the real-time performance of intelligent clothing design in a multicore environment has been improved to a certain extent.

Developments of Adapted Clothing for Physically Disabled People with Scoliosis Using 3D Geometrical Model

Scoliosis is a deformity of the spine that causes disorders of the rib cage. This makes it difficult to design clothes for affected people without following the shape of the rib cage. This paper presents a new 3D clothing design method based on virtual reality for women with physical disabilities such as scoliosis. The current design method is a variation of the draping techniques commonly used by fashion designers to design clothes on a mannequin or human body. However, the current design process highly considers the skeleton and body scan of the person. The skeleton is used to detect the anthropometric points of the patient, while the body scan allows us to detect the morphological contours at the onset of scoliosis. Thus, both allow us to accurately track the patient’s morphology and atypical shape. The position of the morphological contours is indicated by reference marks that are closely associated with the skeleton. This helps to automatically adapt the garment to the evolution of the patient’s pathology over time. The process of creating the 3D garment was processed based on the 3D model of the thorax, which helps to easily determine the anthropometric points and the morphological curves. Using this data, the geometrical model of the garment could be created with 3D ease allowances. The 2D block pattern was then obtained by flattening the 3D patterns using flattening methods. Finally, various tests were performed considering the evolution of pathology to predict the future garment. These tests validate our geometrical model of the garment with 3D ease allowances by comparing the results with previous work.

Fusion Mode and Style Based on Artificial Intelligence and Clothing Design

With the upgrading of intelligent manufacturing, industrial robots will play an important role in the garment industry. The purpose of this article was to study the pattern and style based on the integration of artificial intelligence and clothing design. In this article, the digital modeling of clothing design and the case analysis of intelligent clothing design are described using the method of comparative experiment. The experimental results are obtained from the analysis of fuzzy number of clothing design language evaluation, three-dimensional human body construction clothing size, clothing design elements and auxiliary functions, and the analysis of the advantages and disadvantages of clothing design system. The popular clothing sample is D4 (0.4862), which is 20% higher than other products. It can be concluded that the model proposed in this article can grasp the needs of consumers and select the right one according to the market positioning. The fabric mass production fashion brand can significantly improve the efficiency and satisfaction of the fabric selection decision-making process. It provides enough technical support and style model for intelligent clothing design.