• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.11
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• pp.1771-1781
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• 2008

The purpose of this study was to classify the casual image by clothing design elements. This research was done by survey method with 30 kinds of casual image photos selected in fashion magazines. The data was analyzed by Reliability Analysis, Factor Analysis, ANOVA, Duncan's test and MDS. The results of this study are as follows: 1. Casual image was classified by 6 factors. Those were classic-casual, modern-casual, romantic-casual, vintage-casual, sexy-casual and active-casual images. 2. Classic-casual image was well-expressed by A silhouette, fit, chromatic and chromatic color coordinations and hard texture. Modern-casual image was well-expressed by H silhouette, fit and achromatic and achromatic color coordinations. Romantic-casual image was well-expressed by A silhouette, fit and soft texture. Vintage-casual image was well-expressed by H silhouette, combination apparel-fit, chromatic and chromatic color coordinations and fade-out texture. Sexy-casual image was well-expressed by fitted silhouette, tight apparel-fit and combination texture. 3. Casual image was positioned into mostly dynamic and modern on image scale.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.354-368
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• 2020

Accurate and versatile image data-sets are essential for fashion AI research and AI-based fashion businesses based on a systematic attribute classification system. This study constructs a color and texture attribute hierarchical classification system by collecting fashion item images and analyzing the metadata of fashion items described by consumers. Essential dimensions to explain color and texture attributes were extracted; in addition, attribute values for each dimension were constructed based on metadata and previous studies. This hierarchical classification system satisfies consistency, exclusiveness, inclusiveness, and flexibility. The image tagging to confirm the usefulness of the proposed classification system indicated that the contents of attributes of the same image differ depending on the annotator that require a clear standard for distinguishing differences between the properties. This classification system will improve the reliability of the training data for machine learning, by providing standardized criteria for tasks such as tagging and annotating of fashion items.

• Fashion & Textile Research Journal
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• v.15 no.3
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• pp.336-346
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• 2013

This study focuses on 'texture' as one of the most important fashion and textile design elements; in addition, it proposes various applications of it. Surface texture is indispensable in fashion and textile design that also factors heavily into innovative creations. Along with technological advances in the fashion industry, surface texture has derived many new and attractive features that provide more opportunities for designers to show various design concepts. Rather than the surface quality of fabrics, surface texture in fashion design creates its identity through a manipulation of materials- an application that tends to be primarily for visual effects without being restricted to decorative purposes. The status and significance of surface texture in various creative fields is explored and the evolution of surface texture is traced by analyzing a number of fashion design cases with representative surface textures. The latest feature of surface texture in fashion and textile design is identified to establish a new classification of surface texture with five groups and technical suggestions. This study provides a theoretical basis for this field of study and a new framework that can be employed in the development of surface textures that use innovative techniques as well as the future application of newly-developed textures.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.5
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• pp.533-544
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• 2003

The purpose of this study was to provide practical information to design woolen fabrics in terms of structural and surface characteristics, which produce texture images of fabrics. The relationship among structural, surface characteristics and texture images, and preference and purchase intention were analyzed. To evaluate the texture images of the fabrics subjectively, 7 rank＇s semantic differential scale questionnaires were developed with thirty adjective pairs. Blind and non-blind test were performed with 320 female subjects who were in their 20-30＇s. Commercially available 48 woolen fabrics were used as specimens. Results showed that five factors were obtained: classic, elegance, warmth, natural and casual. These factors were closely related to fiber type, weave type, fabric counts, and finishes.

• Journal of the Korean Society of Clothing and Textiles
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• v.11 no.1
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• pp.29-42
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• 1987

This study was an attempt to survey, the relationships between women's values and preference in clothing design. For the measurement of values scale was to relect the theoretical, economic aesthetic, social. political and religious values explained by Allport-vernon- Lindzey. The preference rate in clothing design consisted of 50 items and 3 factors including color, form and texture. The questionnaire were administered to a sample of women (between college students and adult) who lined in Seoul, Korea. The date for 910 respondents were analyzed by person's carrelation coefficient, to-test and $x^2$ test. Through this study, the followings were founds; 1. Aesthetic value was the mast important of female college students values and economic value was the most important of adult's values. 2. There were significant relation between values and the preference for clothing form in line and style; 1) In line preference, adult women indicated negative correlation with religious values but positive correlation with aesthetic and political values. 2) In style preference, adult women indicated negative correlation with economic values positive correlation with social values, for female college students indicated positive correlation with aesthetic social and political values. 3. There were significant relation between values and preference for texture in touch, thickness, weight, light and luster; 1) In relationship between texture and values, adult women indicated touchness preference negative correlation with theoretical and religious values, for female college students indicated positive correlation with aesthetic and social values. 2) In thickness preference adult women indicated negative correlation with theoretical values but female college students indicated positive correlation with political values. 3) In weight preference, adult women indicated negative correlation with theoretical values. But female college students indicated positive correlation with religious values. 4) In brightness preference, only adult women indicated positive correlation with social values, negative correlation with economic values. In transparency preference, adult women indicated positive correlation with aesthetic values, negative correlation with religious values. 4. There were significant correlation among color and economic, aesthetic; political and religious values, that is, evacuation and economic political values in adult women there were positive correlation with religious values in female students. 1) In chroma only adult women indicated negative correlation with religious values. In warm and cold, positive correlation with economic values in both of them. 2) In coloration, adult women like a complement color indicated negative correlation with aesthetic values, but positive correlation with political values. 5. There were significant differences in the preference of clothing design between female college students and adult women; correlationship with color variables. Evacuation, both of them indicated negative correlation with chroma positive correlation with warm and cold and coloration. In chroma, adult women indicated negative correlation with coloration and warm and cold, for female students indicated negative correlation with coloration. 6. Comparison with clothing preference: 1) In color preference, adult women liked the most white, brown, blue and black in sequence. Female college students liked the most white, also the next is blue and pink. 2) Clothing design preference, there was significant difference in warm and cold and coloration, adult women more liked than female students. In shape of clothing, both of them indicated significant difference in line and style, female students more liked sporty style. In texture, adult women more liked soft thin light weight and bright. 3) In silhouette preference, the most is H-line, female college students more liked.

• Journal of the Korean Society of Clothing and Textiles
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• v.9 no.1
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• pp.9-16
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• 1985

This study was an attempt to survey, the relationships between women's self-concept and preference in clothing design. For the measurement of the self-concept scale was to select the somatic self and the social self which were explained Jung Won Sik's. The preference rate in clothing design consists of 58 items and 3 factors. (color, form, and texture). The questionnaires were administered to a sample of women (between the ages of 20 and 50) who lived in Seoul, Korea. The data for 658 respondents were analyzed by Pearson's correlation coefficient, $x^2$-test, F-test and Duncan-test. Through this study, the followings were founds: 1. There were significant relations between the self-concept and the preference for clothing color in value, chroma and warmth. 2. There were no significant relations between the self-concept and the preference for clothing form in line, silhouette and style. 3. There were significant relations between the self-concept and the preference for texture in touch, thickness, weight and luster. 4. There were significant differences in the preference of clothing design according to their age. That was largely devided into two groups; one's 20' s and the others 30's$\~$40's.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.2
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• pp.109-122
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• 2019

The purpose of this study is to examine the clothing component information and attributes as the control parameters for the 3D modeling process of the biomorphic clothing sculpture using a parametric methodology. The 3D modeling parameters of biomorphic clothing sculpture were identified as exaggerated silhouette, surface texture, and digital color. The types of exaggerated silhouettes were shoulder and hip exaggeration, shoulder exaggeration, hip exaggeration, vertical exaggeration, and horizontal exaggeration. The types of surface texture were embossed, lacy, furry, and complex textures. The types of digital color were chrome, blur, blend, and acid colors. The characteristics of morphological representation due to the attributes of these control variables were identified as morphological variation, organic morphology, organizational morphology, and realistic morphology. As a result, it was found that the parameter attributes were applied to the biomorphic clothing sculpture parametric design process and developed into various shapes.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.3
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• pp.494-504
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• 2008

The purpose of this study was to classify the romantic image by clothing design elements. This research was done by survey method with 20 kinds of romantic image photos selected in fashion magazines. The data was analyzed by Reliability Analysis, Factor Analysis, ANOVA, Duncan's test and MDS. The results of this study are as follows: 1. Romantic image was classified by 4 factors. Those were sexy-romantic, retro-romantic, natural-romantic and cute-romantic images. 2. Sexy-romantic image was well-expressed by fitted silhouette, achromatic and achromatic color coordinations and see-through texture. Retro-romantic image was well-expressed by X silhouette, achromatic and achromatic color coordinations and see-through or combination texture. Natural-romantic image was well-expressed by A silhouette and chromatic and achromatic color coordinations. Cute-romantic image was well-expressed by A silhouette and soft or combination(silky and soft) texture. 3. Romantic image was positioned into mostly traditional or artificial on image scale.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.8
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• pp.1222-1233
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• 2006

The purpose of this study was to classify the modern image by clothing design elements. This research was done by survey method with 25 kinds of modern image photos selected in fashion magazines. The data was analyzed by Reliability Analysis, Factor Analysis, MANOVA, One-Way ANOVA, Duncan's test and MDS. The results of this study are as follows: 1. modern image was classified by 5 factors. Those were sexy-modern, elegant-modern, natural-modern, mannish-modern and minimal-modern images. 2. Sexy-modern image was well-expressed by chromatic and chromatic color coordinations. Elegant-modern image was well-expressed by fitted silhouette, fit and achromatic and chromatic color coordinations. Natural-modern image was well-expressed by A silhouette, loose apparel-fit, chromatic and chromatic coordinations and soft texture. Mannish-modern image was well-expressed by H silhouette, loose apparel-fit, chromatic and chromatic color coordinations and hard texture. Minimal-modern image was well-expressed by H silhouette, tight or loose apparel-fit and soft texture. 3. modern image was positioned into mostly hard or masculine on image scale.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1516-1523
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• 2004

The purpose of this study were to analyze the effect of weft knit structural characteristics on the subjective texture and sensibility. For this, the material was knitted into 8 kinds of weft plain knit fabrics with four kinds of fiber components such as wool, acryl, rayon, and nylon, 3 steps of densities and 3 steps of twist numbers to ply two yarns. The data were analyzed by factor analysis, ANOVA and multidimensional scaling. From factor analysis, subjective textures were categorized as 'bulk/resilience', 'surface/density' and 'soft/drape', and subjective sensibilities were categorized as 'natural/comfortable', 'feminine/elegance' and 'stable/neat' Among the knit structural characteristics, the component of fibers and the density of fabrics were the important factors to give variations in texture and sensibility : In comparison with wool knit of medium density, the knit fabrics of other components and different densities each showed a unique texture and sensibility. But twist number to ply two yams had a few influence on subjective properties. As a result of MDS analysis, the texture and sensibility of plain weft knit fabrics was classified as 'thin-full', 'hard-soft', 'young-old' and 'warm-cool'.