• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.133-143
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• 2002

The textile industry is petting increased effort to manufacture the value-added products that gives the differentiated characters at every level of fiber and fabric production. The color is an important element to be used strategically in order to push up the value-added design. The colors of apparel products have a close relationship with the skin colors of consumers and their preference colors. This study was carried out to cluster the skin colors of the Korean women into several similar skin colors and to analyze their preference colors by the classified groups. We measured the skin colors of 354 Korean women. With color spectrometer, JX-777, we measured 4 points of the body; cheek with removing cosmetics off, forehead, rear neck and arm on the interior part near elbow. All subjects had been shown with 40 color chips and answered the preference colors and preference colors of apparel. Data were analysed to classify skin colors using K-means Cluster Analysis and Duncan test, Frequency and Chi square test on the preference colors about the clustered 3 groups. In doing so, we used in SPSS Win 10 statistical package. Findings were as fellows: 1) The skin colors of the Korean women were clustered into YR, R, and Y skin colors. The majority of the subjects, 324 observations had YR skin colors and the subjects were classified into 3 kinds of skin color groups who had YR skin colors. 2) The average skin colors of total 324 subjects was 5.23YR 6.49/4.09 in Munsell Color System(MCS), 66.56 in L value, 10.53 in a value, and 20.67 in b value. 3) The average skin color of Type 1 was 7.98YR 6.24/4.14 in MCS, 64.10 in L value, 15.05 in a value, and 24.0 in b value. For Type 2 was 7.30 YR 6.56/3.28 in MCS, 67.24 in L value, 6.89 in a value, and 18.4 in b value, and Type 3 was 7.01 YR 7.20/4.38 in MCS, 73.53 in L value, L 16.04 in a value, and 24.87 in b value. 4) The average face color of total 324 subjects was 7.31YR 6.65/3.56 in MCS, 68.13 in L value, 9.53 in a value, and 20.18 in b value. 5) The average face color of Type 1 was 4.19 YR 6.92/5.05 in MCS, 70.78 in L value, 13.2 in a value, and 25.32 in b value. For Type 2 was 5.24YR 6.33/3.79 in MCS, 64.94 in L value, 9.84 in a value, and 19.08 in b value. Type 3 was 5.4YR 6.85/4.68 in MCS, 70.1 in L value, 11.73 in a value, and 23.92 in b value. 6) The difference of mean values between the clustered 3 skin color groups showed significantly different except the a value of neck and H value of cheeks and H value of foreheads. 7) All 3 groups showed that the most preference colors and the most preference colors of apparel was 5R 4/14. and their preference colors were much more than the preference colors of apparel.

• Journal of the Korean Graphic Arts Communication Society
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• v.14 no.2
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• pp.115-128
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• 1996

In this paper, we describe the Color Correction and Preferred Skin Color Reproduction in a ink-jet color printer. The fundamental color correction that converts RGB densities into GMY densities has been ordinarily used. This method can reduce the hue error, but color difference between the preferred skin colors and hardcopy skin colors are large. We have been able to reduce color differences between original skin color and hardcopy skin color by transforming hardcopy skin colors` coordinates into Preferred Skin Colors` coordinates. Experimental results show that the described method is useful and valid for the skin color reproduction in a digital color printer.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.11
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• pp.1338-1349
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• 2003

The color of apparels has the close interdependency on the skin colors of the wearers. This study was carried out to group the skin colors of Korean males into several similar skin colors and to analyze their preference colors. The skin colors were measured quantitatively and classified into several clusters that has similar hue, value and chroma with Munsell color system that is internationally used to communicate the colors. Sample size was 420 Korean males. With color spectrometer, JX-777, 4 points of the body were measured. All subjects had been shown with 40 color chips and answered their preference colors. Data were analysed by K-means Cluster analysis, Duncan test, Frequency and Chi square test using SPSS WIN 10 statistical package. Findings were as follows: 1. The skin colors of Korean males were mixed with skin colors of YR, R, and Y. 2. 420 subjects who have YR color were clustered in 3 kinds of skin color groups. 3. The average face color of total subjects was 4.81YR 5.91/4.97 in Munsell color system, 60.74 in L value, 13.71 in a value, 24.54 in b value. 136 observations out of 420 subjects were composed of Type 1: 4.50YR 6.35/4.87 and 192 observations were composed of Type 2: 4.62YR 5.86/5.12 and 92 observations were composed of Type 3: 5.67YR 5.37/4.79. 4. The average skin color of total 420 subjects was 6.26YR 6.07/4.41 and 62.33 in L value, 10.64 in a value, 23.48 in b value. The average skin color of Type 1 was 6.27YR 6.44/4.27 and of Type 2 was 6.15YR 5.91/4.49 and of Type 3 was 6.49YR 5.84/4.43 respectively. 5. 3 groups showed that the most preference color of sport$.$casual was 2.5Y 8/16 and 7.5PB 4/16 and the most preference color to their skins was 7.5PB 4/16 and 7.5YR 7/16.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.959-967
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• 2005

The color of apparels has the interaction of the face skin colors of the wearers. This study was carried out to classify the face skin colors of Korean males into several similar face skin colors in order to extract favorable colors which flatter to their face skin colors. The criterion that select the new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured quantitatively and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 418 Korean males and other 15 of new males subjects. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 418 subjects who have YR colors were clustered into 3 kinds of face skin color groups. 2. Discriminant variables of face skin colors was 4 variables : L value of forehead, v value of cheek, c value of forehead, and b value of cheek from standardized canonical discriminant function coefficient 1 and c value of forehead, L value of forehead, b value of cheek. and L value of cheek from standardized canonical discriminant function coefficient 2. 3. Hit ratio of type 1 was $92.3\%$, of type 2 was $96.5\%$ and of type 3 was $92.6\%$ by the canonical discriminant function of 4 variables. 4. The canonical discriminant function equation 1 and 2 were calculated with the unstandardized canonical discriminant function coefficient and constant, the cutting score, and range of the score were computed. 5. The criterion that select the new subjects who have the classified face skin colors was decided.

• The Journal of Advanced Prosthodontics
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• v.10 no.6
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• pp.422-429
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• 2018

PURPOSE. Accurate color matching of maxillofacial prostheses to skin is important for esthetics. A computerized color matching system specific to human skin has recently been developed. The purpose of this study was to evaluate the accuracy in color and translucency matching of the computerized color matching system across different skin colors. MATERIALS AND METHODS. The silicone was colored to simulate 28 different skin colors (n=5) to serve as "target skin colors". Using a spectrocolorometer (e-skin), color codes were determined for "replicate skin color" fabrication. CIELAB Delta-E between target skin color-replicate skin color pairs and translucency parameter were calculated. CIELAB Delta-E values were compared with one-way ANOVA and Tukey multiple-comparison. The agreement between $L^*$, $a^*$, $b^*$ and translucency parameter of target skin colors and replicate skin color were calculated by a two-way mixed average measures intraclass correlation coefficient. Translucency parameter of target skin color- replicate skin color pairs were compared with Paired t-test (${\alpha}=.05$). RESULTS. The mean CIELAB Delta-E value was 3.83 and significant differences were found among colors. The intraclass correlation coefficient showed excellent reliability for $L^*$, $a^*$, $b^*$ and good reliability for translucency parameter (P<.001). The mean translucency parameter of replicate skin colors was significantly higher than that of translucency parameter. CONCLUSION. The computerized color matching system specific to human skin was found to be reliable in terms of color and translucency between target skin colors and replicate skin color.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.2
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• pp.303-314
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• 2002

The colors of apparel have become an important element to be used strategically in order to give differentiated character at the level of fiber and fabric production. The colors of apparel have a close relationship with the skin colors of consumers and their preference colors. This study was carried out to classify the skin colors of Korean elderly women into several similar skin colors and to analyse their preference colors. Sample size was 471 Korean elderly women. With color spectrometer, JX-777, we measured 4 points of the body; cheek with removing cosmetics off, forehead, rear neck and arm on the interior part near elbow. All subjects had been shown with 40 color chips and answered the preference colors of apparel and the preference colors. Data weirs analysed to classify skin colors using K-means Cluster Analysis and Duncan test. Independent variables for Cluster Analysis were 12 variables out of L value, a value and b value of 4 points. In doing so, we used SPSS WIN 10 statistical package. Findings were as follows: 1) The skin colors of the Korean elderly women were composed of skin colors of YR, R, and Y. 2) 355 subjects were classified into 4 kinds of skin color groups. 3) The average face color of type 1 was 6.7YR 5.1/4.3 and 56 observations out of 355 subjects were composed of Type 1 and of Type 2 was 6.1YR 6.1/4.5 and 166 observations out of 355 and of 3 Type 6. YR 4.8/4.2 and 75 observations out of 355 and of Type was 6.17 YR 5.7/4.7 and 58 observations out of 355. 4) The average skin color of Type 1 was 7.0YR 5.9/4.4 and of Type 2 was 7.2YR 6.3/4.2 and of Type 3 was 7.0YR 6.2/4.2 and of Type 4 was 7.6YR 5.4/4.2 respectively. 5) The mean values of 12 variables between the 4 classified face color and skin color groups showed significantly different except H value of skin color. 6) All 4 groups showed that the most preference color of apparel and the most preference color were 2.5R 5/14 respectively.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.978-986
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• 2005

The color of apparel products have a close relationship with the face skin colors of consumers. In order to extract the favorable colors which flatter to consumer's face skin colors, this study was carried our to classify the face skin colors of Korean females. The criteria that select new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 324 Korean females and other new 10 college girls. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 324 subjects who have YR colors were clustered into 3 face skin color groups. 2. Discriminant variables of face skin colors were 5 variables : b value of cheek, V value of forehead, L value of cheek, C value of forehead and H value of cheek by the standardized canonical discriminant function coefficient 1. 3. Hit ratio of type 1 was $96.8\%$, of type 2 was $94.9\%$, of type 3 was $100.0\%$ and mean of hit ratio was $96.9\%$ by canonical discriminant function of 5 variables. 4. With the unstandardized canonical discriminant function coefficient and constant, canonical discriminant function equation 1 and 2 were calculated. And cutting score and range of score of the classified types were computed. The criteria that select the new subjects were decided.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.3
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• pp.516-524
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• 2001

This dissertation has been intented to grasp the components of personal colors and classify personal colors. The Method of the study was quasi-experimental. In the experiment to evaluate personal colors, the subjects was 315 male and female college students in Taegu and Kyungbuk area. The evaluations were analyzed by SAS and the methods used were descriptive statistics, cluster analysis, T-test. The results obtained were as follows: First, the major components of subjects personal colors were found to be the colors of skin and hair. Secondly personal colors were classified into three types: warm, cool, and ambiguous. Third types of personal colors tended to be different between men and women.

• Proceedings of the Korea Society of Costume Conference
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• 2003.10a
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• pp.39-39
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• 2003

The currently used personal color analysis is mostly based on Westerners' skin colors. As a result, the suggested colors are often not suitable for Korean people's skin colors. Accordingly, the purpose of this study is to develop 'Personal Color Design System(PCDS)' that can suggest fashionable colors suitable for Korean skin colors and personal color types. For this, the system was verified by customers testing and questionnaires, while the system modification and complementary measures were conducted.

• Fashion & Textile Research Journal
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• v.10 no.6
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• pp.1014-1022
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• 2008

This study focuses on practical appliance of color therapy to skin care. After visiting the notion of color therapy and skin care, this study considers the ideas and background theories for diagnosis of constitution and skin. Cosmic duals force five element theory developed in China was the first introduction; Ayurvedic medicine and seven chakra notion are examined. Cosmic duals force five element theory, an idea describing the composition and movement rule of the cosmic components, adopted five colors(white, yellow, red, blue, and black) for cure purposes. In future, mental effect of the color is examined in the latter part of this study. The practice of the color therapy assigns solarized cream treatment and photo therapy, simultaneously proposes the use of color therapy to the skin care. For the diagnosis of the constitution, cosmic duals force five element theory and ayurvedic medicine are followed in a sequence. Cosmic duals force five element theory introduces five colors. Constitution medicine considers four types, ayurvedic medicine adopts three types, and seven colors are mentioned as chakra colors. Such a variations lead to possible disagreement on constitution analysis and driven colors. This study adopts the above methodologies for selecting potential color therapy for skin care. Adopt of selected cases are purely a part of the proposal. Initially, examined theories serve as a pilot for selecting a representative hypothesis. Followed selection of constitution and matched color for the use of the skin care are the scope of this study. In summary, background methodologies are implemented for the calculation of color therapy.