• Fashion & Textile Research Journal
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• v.11 no.1
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• pp.103-111
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• 2009

This study is to help make-up and coordination for image-making after analysis of facial color and shape of elderly women. The data was analyzed 55-75 years old 212 elderly women's face color and pictures by means of SPSS 12.0 statistics package. On the basis of the colorimetric data on face by Minolta CM2500D, this research considered the analysis of facial color, patternization of facial color and its analysis by age group; for the analysis of facial shape, this research patternized facial shape and analyzed its characteristic using both contour-based facial shape analysis and Kamata facial shape analysis. As for facial color, it was found that the lower age bracket has bright and reddish face, looking fine, while the higher age bracket has a conspicuously yellowish face, looking bad. The community of facial color is classified as 3 types and it was found out that the facial color of the subjects belonging to Type 3, whose L value is the largest, looked the brightest; the face of the subjects belonging to Type 2, whose a value is the largest, was much tinged with red, and the face of the subjects belonging to Type 1, whose b value is the largest were tinged with yellow. According to the analysis of facial shape, there appeared oval & long forms in the classification by contour, while there appeared a lot of downward-directed power and inner-directed power in the classification by Kamata, which is believed to reflect the phenomenon that their chin line becomes roundish and the facial length also tend to be longer due to aging.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.57-60
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• 2002

Facial features are often used for human computer interface(HCI). This paper proposes a method to detect facial features using color and facial geometry information. Face region is first extracted by using color information, and then the pupils are detected by applying a separability filter and facial geometry constraints. Mouth is also extracted from Cr(coded red) component. Experimental results shows that the proposed detection method is robust to a wide range of facial variation in position, scale, color and gaze.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1128-1141
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• 2009

Graphical expressions are continuously improving, spurred by the astonishing growth of the game technology industry. Despite such improvements, users are still demanding a more natural gaming environment and true reflections of human emotions. In real life, people can read a person's moods from facial color and expression. Hence, interactive facial colors in game characters provide a deeper level of reality. In this paper we propose a facial color adaptive technique, which is a combination of an emotional model based on human emotion theory, emotional expression pattern using colors of animation contents, and emotional reaction speed function based on human personality theory, as opposed to past methods that expressed emotion through blood flow, pulse, or skin temperature. Experiments show this of expression of the Facial Color Model based on facial color adoptive technique and expression of the animation contents is effective in conveying character emotions. Moreover, the proposed Facial Color Adaptive Technique can be applied not only to 2D games, but to 3D games as well.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.147-149
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• 2004

There are no authentic solutions in a face region extraction problem though it is an important part of pattern recognition and has diverse application fields. It is not easy to develop the facial region extraction algorithm because the facial image is very sensitive according to age, sex, and illumination. In this paper, to solve these difficulties, a fuzzy color filer based on the facial region extraction algorithm is proposed. The fuzzy color filter makes the robust facial region extraction enable by modeling the skin color. Especially, it is robust in facial region extraction with various illuminations. In addition, to identify the fuzzy color filter, a linear matrix inequality(LMI) optimization method is used. Finally, the simulation result is given to confirm the superiority of the proposed algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.6 s.154
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• pp.971-980
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• 2006

The colors of apparel have a close relationship with the facial color types of consumers. To extract the favorable colors that flatter to consumer's facial color types, the facial colors of Korean females were analyzed. With color meter JX-777, 2 points of face were measured and classified into 3 clusters that had similar hue, value and chroma. Other new 10 college girls were measured and 3 subject among them were selected by the criteria that choose new subjects who have the classified facial color types. 175 respondents answered the degree of becomingness of color samples on three subjects. Data were analyzed by K-means cluster analysis, ANOVA and Duncan multiple range test using SPSS Win. 12. Findings were as follows: 1) 324 subjects who had YR facial colors were classified into 3 facial color groups. The average facial color Type 1 was 4.82YR 6.47/3.70 and composed 48.88% among total observations. Type 2 was 5.99YR 6.12/4.12 and 30.25%. Type 3 was 5.15YR 7.07/4.97 and 20.99% respectively. 2) Favorable colors for Type 1 were 18 colors that belonged to 'a' group from among colors that were divided into a, b, c group by Duncan post hoc test. 3) Type 2 showed that this type had many unfavorable colors. Unfavorable colors were 18 colors that belonged to 'c' by Duncan test. 4) Type 3 showed that black is the most favorable color and 18 colors were at middle level, which belonged to 'b' from among 18 colors that were divided into a, b, and c by Duncan test.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.2 s.150
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• pp.316-325
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• 2006

The colors of apparel are getting more important to give the differentiated character on fiber and fabrics. This study was to extract the favorable colors that become to facial color types. Research was carried out to classify the facial colors into several similar facial color groups. With JX-777, 2 points of face: forehead and cheek, were measured and classified into 3 facial color types. Sample size was 418 Korean adult males and other 15 of new males subjects. New chosen 3 subjects who had the classified facial color types, wore silver gown and black hat on his head to minimize the interaction of the clothe color an hair. The 40 standardized color samples were used to extract the favorable colors. 187 respondents answered the degree of becomingness of color samples on 3 facial color types. Data were analyzed by K-means cluster analysis, ANOVA and Duncan multiple range test using SPSS Win. 12. Findings were as follows: 1. 418 subjects who had YR colors were classified into 3 kinds of facial color groups. Type 1 was 4.59YR 5.89/5.12, Type 2 was 5.61 YR 5.41/4.79 and Type 3 was 4.38YR 6.49/4.89 respectively. 2. Favorable colors for Type 1 were 2 colors that belonged to ' a ' group from among colors that were divided into a, b, c group and 18 colors that belonged to ' a ' group from among colors that were divided into a, b group by Duncan post hoc test. 3. Type 2 showed that this type had many unfavorable colors. Unfavorable colors were 16 colors that belonged to ' c ' by Duncan test. 5. Favorable colors for Type 3 were 14 colors that belonged to ' a ' from among colors that were divided into a, b, c and 16 colors that belonged to ' a ' from among colors that were divided into a, b by Duncan test.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.22 no.2
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• pp.141-152
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• 1996

Many eastern females concern themselves about the condition and the color of their skin. The purpose of the present study is to classify the skin trouble and the change of the facial color due to hormonal cycle in female. We examined the actual cricumstances by questionnaires, and made patch tests of methyl nicotinate, representing rubefacient, to estimate the epidermal penetratin rate, and measured the facial color change during the menstrual cycle period to invest the correlation factors between skin trouble due to cosmetics and facial color change. Fifty-two percent of subjects had skin trouble relating to cosmetics. One second of subjects with skin trouble due to cosmetic complained the change of sysptom by menstrual cycle. The changes of systptom were related on premenstrual period. The skin trouble developed mainly on the first trimester of the pregnancy. In patch test of methyl nicotinate, most cases showed decreased threshold of the reaction on minstruation, and other cases showed increased reactivity of the skin of menstruation. In facial color measurements, it proves in the appearance of red spot, darkness, increasing the value and turning the hue to yellowish, Also it demonstrates that premenstruation hue turn red and value level decrease. During the period, facial color turns pale and hue progress to yellow. This fact coincides with the questionnaire. We have quqntified through questionnaire, which demonstrates it has good correlation with done to the subjects among the internal environment factors hormonal cycle influences the facial color change and the skin trouble due to cosmetics. Through this paper the development of an more fragmented make-up and skin care products is required to increase the interest to females, to make true the creation of beauty.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

• The Research Journal of the Costume Culture
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• v.20 no.2
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• pp.144-153
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• 2012

This study performed a simultaneous sensory evaluation and color measurement, targeting 136 female university students who live in the Dae-Jeon region. the study measured participants'facial coloration under the condition of available light between 11 AM and 3 PM from Spring (May) to Autumn (October) in 2009. For statistical analysis, descriptive statistics, a member variate analysis, and discriminant analysis were executed using SPSS version 18.0 of the statistics program. The results of this study are as follows. First, as a result of the sensory evaluation, the blue undertone well matched to face type was dominantly distributed among the female university student participants. Second, the forehead showed a type of yellowish coloration and was relatively dark to cheeks. However the cheek displayed a reddish coloration and was relatively bright compared to the forehead from an evaluation of a cheek and forehead color measurement. Third, due to the investigation the of facial coloration variable, a yellowish and reddish chromaticity on the cheek were evident as a variable of facial coloration, which has an influence on the classification of the types of facial color. As a result of the induced discriminant through these two color variables, the yellowish chromaticity appeared as a color variable to have a greater influence than the reddish chromaticity on the cheek.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.69-72
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• 2002

Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.