• 한국의류산업학회지
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• 제11권1호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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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.

• 한국멀티미디어학회논문지
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• 제12권8호
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• pp.1128-1141
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• 2009

게임 산업이 성장하면서 게임 그래픽 분야는 가장 빠르게 발전하고 있으며 지금은 실제 사진과 컴퓨터 그래픽을 구분하기 힘든 정도로 그래픽 기술은 양적으로나 질적으로 성장했다. 그러나 이러한 발전에도 불구하고 새롭게 출시되는 게임에 등장하는 캐릭터는 정서를 표현하지 않거나 소극적으로 표현하고 있다. 일반적으로 사람들은 얼굴의 표정이나 얼굴의 색(안색)에서 많은 정서 정보를 인지하는 것은 누구나 아는 사실이다. 그러므로 컴퓨터의 게임 환경에서 등장하는 캐릭터에게도 얼굴의 색의 변화를 통하여 유저에게 게임의 사실적인 느낌을 줄 수 있다. 본 논문에서는 기존의 맥박과 피부 온도만을 이용한 방법과는 다른 인간의 정서 이론을 기반한 정서 모형과 애니메이션의 정서표현 색 그리고 성격이론을 기반한 정서의 반응 속도를 결합하여 게임 캐릭터의 얼굴의 색을 동적으로 변화시켜 정서를 표현할 수 있는 얼굴 색 적응 기술 (Facial Color Adaptive Technique: FCAT)를 제안한다. 실제 얼굴 색 적응 기술을 이용하여 만든 얼굴색 모형(Facial Color Model : FCM)과 애니메이션 콘텐츠의 정서표현을 비교한 결과 정서 표현 색상과 변화율이 애니메이션과 유사하게 시뮬레이션 되었다. 또한 2차원 이미지뿐만 아니라 3차원 이미지에도 적용이 가능함을 확인 하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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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.

• 한국의류학회지
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• 제30권6호
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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.

• 한국의류학회지
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• 제30권2호
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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.

• 대한화장품학회지
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• 제22권2호
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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.

• 인터넷정보학회논문지
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• 제3권6호
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• pp.13-24
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• 2002

본 논문에서는 색상 정보와 변형 모델을 이용한 얼굴 영역 및 얼굴의 특징 영역의 자동 검출 방법을 제시한다. 영상으로부터 획득할 수 있는 정보 중 가장 빠르고 쉽게 얻을 수 있는 정보가 색상 정보이며, 색상정보는 사물을 판단함에 있어서 가장 효율적이면서 컴퓨터의 계산량을 줄일 수 있다는 장점을 갖고 있기 때문에 얼굴 영역 검출 방법으로 많이 이용되고 있다. 본 연구에서는 얼굴영역 및 얼굴 특성 추출함에 있어 컬러모델 사용 시 외부 조명의 영향을 줄여주는 조명 보정 방법을 제시하고, 조명 보정에 의해 평활화 된 YCbCr 색상모델에 적용하여 각 성분 특성을 고려한 얼굴영역 및 얼굴의 특성 영역에 해당하는 후보 영역을 검출하는 방법을 제시한다. 검출된 얼굴후보 영역 및 특성 영역은 가변 모델인 동적 윤곽선 모델의 초기 값으로 자동 적용되어 윤곽선 모델 적용 시 문제점가운데 하나인 초기 값 설정문제를 해결함과 동시에 얼굴 및 얼굴 특징 정보의 정확한 윤곽선을 추출하는데 사용된다. 실험 결과 제시된 방법을 적용한 결과 빠르고 효과적으로 얼굴 및 특성 영역을 검출 할 수 있음을 입증 할 수 있었다. 이상에서 추출된 얼굴의 특성정보는 차후 얼굴 인식 및 얼굴 특성을 설명하는 얼굴 특성 서술자로 사용될 수 있다.

• 복식문화연구
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• 제20권2호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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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.