• Fashion & Textile Research Journal
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• v.5 no.3
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• pp.283-288
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• 2003

Large quantity of metal mordant in natural dyeing has been used. For environmental reason, there is a need to reduce the amount of metal mordant and suggest the optimum amount of metal mordant in dyeing process. In this study, the relationship between mordant concentration and dyeing property was investigated. Various metal mordant concentrations of AI, Cu, Fe, Sn, were studied (from 1 to 5%). After treatment of mordant on cotton fabric, the concentration of metal ion in used mordant solution was quantified. There was no significant difference of the tone of color in mordant concentration from 1% to 5%, Therefore, there is no need to increase mordant concentration over 1%. chitosan treated cotton fabric showed a significant increase in dyeing affinity compared to untreated cotton fabric (the value of ${\Delta}E$ was 20). chitosan increased dye affinity significantly in the presence of mordant. It can be suggested that chitosan itself can replace metal mordants in the future.

• Electronics and Telecommunications Trends
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• v.39 no.3
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• pp.107-115
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• 2024

Image synthesis has been remarkably developed in the computer vision domain and various researches have been proposed to generate realistic and high-resolution images. In particular, image-based virtual try-on is an application in fashion domain to simulate wearing clothes. Specifically, using input images of a fashion model and products, an realistic image of the model wearing the provided garments is synthesized. In this paper, we present a comprehensive review of technical trends in image-based virtual try-on technology. We first introduce relevant datasets and discuss their characteristics. Then, we categorize existing image synthesis methods into three main streams: warping-based methods, encoding-decoding-based methods, and diffusion-based methods. Finally, we explore other important research issues in the field of virtual try-on and analyze related researches aimed to tackling those challenges.

• Journal of Korea Trade
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• v.27 no.1
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• pp.119-138
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• 2023

Purpose - This research is to empirically explore the differences in apparel consumption among male and female teenagers and college students in Korea and China. By conducting a survey to understand customers' needs and behaviors, fashion businesses will be able to improve their customer satisfaction and avoid redundancy, inventory, and the waste of resources, effort and money. Design/methodology - The research design considers the consumption patterns of male and female high school and college students in Korea and China. To analyze the data, the study employs decision trees, a type of machine learning algorithm. A decision tree model was developed to examine the relationship between the explanatory and response variables, which can be either quantitative or qualitative in nature. Findings - The main findings of this study indicate that there are differences in shopping behavior among different customer segments. The results show that men have a simpler shopping behavior compared to women. Additionally, cultural factors and the difference in fashion needs between students and non-students have a significant impact on the shopping choices of Chinese and Korean individuals. Originality/value - Existing studies often assume that the shopping behavior of high school and university students is similar and that there are no significant differences in clothing purchases between men and women across countries. The results provide valuable insights into the unique shopping behavior of different customer segments, and can inform fashion businesses in their efforts to meet the needs of their customers.

• Journal of the Korean Home Economics Association
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• v.44 no.1 s.215
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• pp.25-35
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• 2006

This study investigated the scheme for correctly making Korean fashion design known to the world. It attempted to increase the influence of the Eighteenth Century Costume in contemporary fashion. During the 18th century, France had an almost complete monopoly of fashion. Growing out the fairyland atmosphere of the French Court and often conceived of as ennui by personal vanity, this fashion was a product of an age which sought at any price to live life with supreme grace. Most of the special costume exhibitions in the Metropolitan Museum of Art are planned and directed by Polaire Weissman, Diana Vreeland, Richard Martin, Harold Koda. The Costume Institute has held exhibitions of the Eighteenth Century Costume several times such as "Museum Period Rooms Re-Occupied in Style," "the Eighteenth Century Women," "the Ceaseless Century," "Dangerous Liaisons," etc. Especially, the exhibition of "Dangerous Liaisons" is organized in ten parts such as the Portrait, the Levee, the Music Lesson, the Withdrawing Room, the Broken Vase, the Favorite, the Masked Beauty, the Card Game, the Late Supper, and the Shop. Using the eighteenth century as its touchstone, The Ceaseless Century proceeds differently, not seeking the short distance between a discrete present and the multiple past but rather showing the complicated navigation that comes of revivalism swing to and fro on the timeline of history and sensibility. The designers featured include Karl Lagerfeld, Gianni Versace, Vivienne Westwood, Jean Paul Gaultier, Christian Dior, Cristobal Balencicga, Christian Lacroix, Stella McCartney forChloe, Olivier Theyskens, Alexander McQueen, etc. Therefore, Korean designers should refrain from (Ed-confirm) the foreign collection without a clear purpose and should devote their effort to create with an active attitude.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.13-23
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• 2022

In this paper, we propose a detailed component image classification algorithm by fashion item for unstructured data retrieval in the fashion field. Due to the COVID-19 environment, AI-based online shopping malls are increasing recently. However, there is a limit to accurate unstructured data search with existing keyword search and personalized style recommendations based on user surfing behavior. In this study, pre-processing using Mask R-CNN was conducted using images crawled from online shopping sites and then classified components for each fashion item through CNN. We obtain the accuaracy for collar of the shirt's as 93.28%, the pattern of the shirt as 98.10%, the 3 classese fit of the jeans as 91.73%, And, we further obtained one for the 4 classes fit of jeans as 81.59% and the color of the jeans as 93.91%. At the results for the decorated items, we also obtained the accuract of the washing of the jeans as 91.20% and the demage of jeans accuaracy as 92.96%.

• Fashion & Textile Research Journal
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• v.17 no.4
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• pp.541-549
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• 2015

Korean traditional mask play was done at outdoor to let spectators join the play and take mask at performance and to have disadvantage of poor transfer of dialog to the spectators. Performers transferred dialog directly and/or indirectly by using visual costume, and Tongyeong Ogwangdae with many dialogue expressions concerning the costume made use of proper intention to help spectators understand. In this study, the author watched performance of Tongyeong Ogwangdae to collect and investigate not only image material but also photograph material and to classify intention of the costume into three: First, contents of the dialog were intended to make shape. The costumes of Hongbaek Yangban, Meoktal Yangban and Jorijung of the 2nd section gave spectators contents of the play, and the costume of Halmi Yangban of Nochangtal of the 4th section described dialog of Halmi. Second, dialog had connotative metaphor. The costume of Yeongno of Yeongnotal of the 3rd section symbolized an unfinished dragon, while that of Halmi of Nongchangtal of the 4th section did sacred of Halmi. And, Nongchagtal Ai's costume of the 4th section prayed for value of Ai, richness of the life and fecundity. Third, conflict between characters was intended by indirect media. The costume of Maltukee of metaphor mask of the 2nd section became base of the assertion supporting that Maltukee had better birth history than Yangban had, and the costume of Yeongnoyangban of Yeongnotal of the 3rd section produced conflict at disclosure of identity.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.

• Convergence Security Journal
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• v.23 no.4
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• pp.61-70
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• 2023

Clustering is an unsupervised learning method that involves grouping data based on features such as distance metrics, using data without known labels or ground truth values. This method has the advantage of being applicable to various types of data, including images, text, and audio, without the need for labeling. Traditional clustering techniques involve applying dimensionality reduction methods or extracting specific features to perform clustering. However, with the advancement of deep learning models, research on deep clustering techniques using techniques such as autoencoders and generative adversarial networks, which represent input data as latent vectors, has emerged. In this study, we propose a deep clustering technique based on deep learning. In this approach, we use an autoencoder to transform the input data into latent vectors, and then construct a vector space according to the cluster structure and perform k-means clustering. We conducted experiments using the MNIST and Fashion-MNIST datasets in the PyTorch machine learning library as the experimental environment. The model used is a convolutional neural network-based autoencoder model. The experimental results show an accuracy of 89.42% for MNIST and 56.64% for Fashion-MNIST when k is set to 10.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.69-82
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• 2023

High-tech sensibility textile and fashion, in which consumers' emotions and various textile and fashion technologies are converged, is an important industrial group. It is important to develop the ability to apply in practice by gathering the creative by understanding other fields and exchanging ideas through interdisciplinary collaboration in the field of emotional engineering. Through interdisciplinary research and collaboration, talent must be nurtured of individuals who would lead the era of the 4^th Industrial Revolution with the ability to empathize with others as well as the creative convergence-type intellectual ability necessary for the rapidly changing society. To determine content-creation methods, basic research is conducted. Additionally, this study investigates on the current status and educational process of the emotional textile-fashion industry worldwide. To nurture talents in the textile and fashion sensibility science, the basic contents are created to manage the knowledge that delivers sensibility science and the ICT related to this field, as well as in the intensive, PB-style conceptual design based on sensibility. The process from derivation of consumer emotion analysis and product development can be experienced through smart kit practice. Moreover, various methods are developed to set up intellectual property rights generated while developing ICT convergence products as start-ups. The study also covers new knowledge rights to develop emotional textile fashion.

• Fashion & Textile Research Journal
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• v.3 no.2
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• pp.162-167
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• 2001

The dyeing powder drawn out from Cinnamoum cassia by water was concentrated. Using this powder, the silk fabrics were dyed and they measured with the K/S value, surface color, dye fastness and antimicrobial properties. The colorant of Cinnamoum cassia was proved flavonoids by FT-IR spectrum. The K/S values of silk by mordants concentration were much higher than those of high-concentration, the color yield of the silk fabrics were most efficient the premordanting method. The surface colors on the dyed fabric depended heavily upon mordants used or mordanting methods. For all cases, the value of the dyed fabric was generally dark except AI-mordant. The chroma produced clear for the unmordanting, the color difference was distinct when using the Fe-mordant. The color fastness was significantly improved when mordants were added. In the case of the light fastness, Cu-mordants improved more than 1-2 level. The Cu-mordant showed the greatest antimicrobial activity on the silk fabric.