This study aims to gather precise information on the real fabric color and texture, and purchasing intention of mobile shoppers buying clothes. Eighty volunteers participated in the sensory test on three smartphones with four colors and two fabricssmooth taffeta and hairy doeskin. This study carried out the posteriori test using the one-way ANOVA and Duncan test by SPSS21.0. In the analysis’ results of color preference, there were no differences among the four colors of taffeta between the smartphones, but different preferences between the red and yellow doeskin exist. In the case of the Samsung phone, which has an immense color distortion, the red fabric has a low color preference. In contrast, on the Apple phone yellow fabric had the highest preference because of its brightness. The Apple phone also has the highest purchasing intention of yellow colored taffeta, which is similar to the color preference results, although the real fabric has the opposite result. For doeskin, the real red and blue colored fabric has the highest purchasing intention. The Samsung phone has the biggest color mismatch with the real fabric. It also has the lowest purchasing intention of red taffeta fabric, while the LG phone has the lowest purchasing intention of blue fabric. Using the paired comparison method of the similarity between ‘real’ fabrics and the mobile version of fabric colors has a low similarity on all four colors of taffeta and doeskin fabrics. Therefore it can be concluded that phones do not represent the ‘real’ fabric color.

This study measured dyeing properties under different dyeing conditions and levels of antimicrobial activity when man-made fibers are dyed with gallnut, including rayon, tencel, tencel blended fabric, soybean fiber, and nylon non-mordanted. The dye up-take (K/S), color (L*a*b*), and color differences (△E) were measured with a colorimeter, and the number of bacteria present in the dyed fabrics were determined using Staphylococcus aureus and Klebsiella pneumonia as strains. The results are as follows: First, the optimal dyeing conditions for man-made fibers dyed with gallnut are 60 minutes of dyeing time and a 80℃ dyeing temperature. Second, gallnut dye is most effective on soybean fiber and then, in descending order of effectiveness, on nylon, rayon, tencel, and tencel blended fabric. This means that dyeing properties of nitrogen containing fibers are excellent when using gallnut. Third, all man-made fibers are dyed brown with gallnut. This implies dyeing possibility of man-made fibers about gallnut dye, so development and supply of natural dyed goods of man-made fibers can be increased. Fourth, in all man-made fibers dyed with gallnut extract, both Staphylococcus aureus and Klebsiella pneumonia show 99.9% reduction ratios of fungistasis, which indicate antimicrobial activity. Therefore, safe, functional, man-made materials can be developed to relieve symptoms from and treat patients with skin ailments.

Mobile shoppers have encountered frequent color mismatch in the products that they have purchased, as they can only rely on their sense of sight. Therefore, fabric color and color difference recognized by smartphone display during mobile shopping were studied using instrument analysis method. It aimed to gather precise information on actual fabric color understanding of the mobile shoppers purchasing textile products. Three smartphones were selected from LG, Samsung, and Apple companies, and four colors were researched (red, yellow, green and blue) to both polyester and wool test fabrics for color analysis though color measuring instruments. The results from the spectrophotometer indicated that the color coordinate location of smartphone fabric color is similarly distributed regardless of the type of fabric. The Samsung smartphone displays a relatively high color chroma (especially on red-colored fabric) regardless of the type of fabric due to a high color reproduction range. In contrast, the LG smartphone, which has high color temperature, displays high color chroma on the blue colored fabric with a significant color mismatch between the actual fabric color and smartphone fabric color. From the results of this study, issues related to mobile shopping can be addressed through an analysis of the products sold, the smartphone’s color representation, and user understanding.

Mobile shoppers have encountered frequent color mismatch in the products that they have purchased, as they can only rely on their sense of sight. Therefore, fabric color and color difference recognized by smartphone display during mobile shopping were studied using instrument analysis method. It aimed to gather precise information on actual fabric color understanding of the mobile shoppers purchasing textile products. Three smartphones were selected from LG, Samsung, and Apple companies, and four colors were researched (red, yellow, green and blue) to both polyester and wool test fabrics for color analysis though color measuring instruments. The results from the spectrophotometer indicated that the color coordinate location of smartphone fabric color is similarly distributed regardless of the type of fabric. The Samsung smartphone displays a relatively high color chroma (especially on red-colored fabric) regardless of the type of fabric due to a high color reproduction range. In contrast, the LG smartphone, which has high color temperature, displays high color chroma on the blue colored fabric with a significant color mismatch between the actual fabric color and smartphone fabric color. From the results of this study, issues related to mobile shopping can be addressed through an analysis of the products sold, the smartphone’s color representation, and user understanding.

This study aims to analyze the changes in the mechanical properties of interlock fabrics knitted with three types of fibers (i.e., cotton, wool, and polyester) by bonding fusible interlinings with varying deniers (i.e., 10D, 20D, and 30D) for a 3D virtual try-on system. We experimented with four properties and thicknesses of twelve specimens of interlining bonded knitted fabrics including face fabrics and interlinings. The results showed that the tensile property changed values (i.e., LT increased, and WT and RT decreased) according to the denier of interlinings; however, the change was slight. On the other hand, the bending property increased significantly as the denier of the interlining increased on both the wale and the course. Among shearing properties, the value of G increased as the denier of the interlining increased on both the wale and the weft; however, 2HG decreased. Additionally, changes in the compression property varied according to the fibers and the denier of the interlinings. The thickness of the knitted fabrics increased or decreased slightly by bonding the interlining. based on these results, we conclude that the 3D virtual system users need to reflect these numerical changes of interlock fabrics by bonding interlinings when they perform fitting tasks on the screen to accurately express the to accurately express the manufacturing conditions of the real garment.

This study aims to analyze the changes in the mechanical properties of interlock fabrics knitted with three types of fibers (i.e., cotton, wool, and polyester) by bonding fusible interlinings with varying deniers (i.e., 10D, 20D, and 30D) for a 3D virtual try-on system. We experimented with four properties and thicknesses of twelve specimens of interlining bonded knitted fabrics including face fabrics and interlinings. The results showed that the tensile property changed values (i.e., LT increased, and WT and RT decreased) according to the denier of interlinings; however, the change was slight. On the other hand, the bending property increased significantly as the denier of the interlining increased on both the wale and the course. Among shearing properties, the value of G increased as the denier of the interlining increased on both the wale and the weft; however, 2HG decreased. Additionally, changes in the compression property varied according to the fibers and the denier of the interlinings. The thickness of the knitted fabrics increased or decreased slightly by bonding the interlining. based on these results, we conclude that the 3D virtual system users need to reflect these numerical changes of interlock fabrics by bonding interlinings when they perform fitting tasks on the screen to accurately express the to accurately express the manufacturing conditions of the real garment.