• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.347-347
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• 2004

• 가정의 벗
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• v.37 no.10 s.434
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• pp.14-15
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• 2004

유니세프 한국위원회에서 일하면서 우리나라도 밥을 제때 먹지 못하는 어린이들이 많은데 피부색도 다른 아이들을 왜 도와주는지 모르겠다는 말을 많이들었다. 세계화가 되는 것이 영어를 잘 하는 것만이 아니라 우리의 저편에서 기근과 질병으로 고통받는 어린이들이들에게 우리의 조그마한 정성을 나누어 주는 것이 아닐까 생각해 본다.

• Archives of design research
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• v.15 no.4
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• pp.327-336
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• 2002

This paper is intended to help cool-skin-colored people to choose suitable clothing colors confidently and look well-dressed and to make positive self-images. A pseudo-experimental method has made it possible to analyze the visual evaluations of clothing color images for cool-skin-colored people and obtain the following results. 1. Reddish colors of vivid tone for doffing give positive images and those of dull and dark tone, negative ones. 2. Yellowish colors of vivid and bright tone for doffing show positive images and those of dull and dark tone, negative ones. Cool yellow of light tone proves to contribute to a well-looking image. 3. Warm green of vivid and deep tone, and cool green of vivid tone for clothing present positive images. 4. Warm blue of vivid and deep tone, and cool blue of vivid and bright lone make positive images. Either blue with dull tone gives a negative image. 5. Purple colors whose tone is vivid, deep and light contribute to positive images, and those of dull tone, negative ones.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.61-71
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• 2004

Recently, various techniques for face detection are studied, but most of them still have problems on processing in real-time. Therefore, in this paper, we propose novel techniques for real-time detection of human faces in sequential images using motion and chroma information. First, background model is used to find a moving area. In this procmoving area. edure, intensity values for reference images are averaged, then skin-color are detected in We use HCr color-space model and adaptive threshold method for detection. Second, binary image labeling is applied to acquire candidate regions for faces. Candidates for mouth and eyes on a face are obtained using differences between green(G) and blue(B), intensity(I) and chroma-red(Cr) value. We also considered distances between eye points and mouth on a face. Experimental results show effectiveness of real-time detection for human faces in sequential images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.105-112
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• 2012

Face detection at a distance faces is very challenging since images are often degraded by blurring and noise as well as low resolution. This paper proposes an improved face detection method with AdaBoost filtering and sequential testing stages with color and shape information. The conventional AdaBoost filter detects face regions but often generates false alarms. The face detection method is improved by adopting sequential testing stages in order to remove false alarms. The testing stages comprise skin-color test and variable edge-mask filtering. The skin-color filtering is composed of two steps, which involve rectangular window regions and individual pixels to generate binary face clusters. The size of the variable edge-mask is determined by the ellipse which is estimated from the face cluster. The validation of the horizontal and vertical ratio of the mask is also investigated. In the experiments, the efficacy of the proposed algorithm is proved by images captured by a CCTV and a smart-phone

• Journal of the Korean Society of Costume
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• v.54 no.7
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• pp.79-90
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• 2004

In this study we tried to find the skin color of Koreans according to the change of seasons, and to the degree of make-up used by men and women. in order to furnish foundation data that could be used in the cosmetics and clothes industries. The skin color was measured with Minolta's Chrome Meter CR-200 in seven parts of the body with Munsell's hue, value, chroma. The difference in skin color in men and women's groups, and the difference in skin color of each group in March and in September were treated with SPSS's Anova and t-test. 1. In both seasons. March and September, a big difference could be observed between the two groups (men and women's). The body was more yellowish than the face. The men's group had a reddish skin color than the women's groups. In all groups we could observe a big difference in color between seasons, and in March, the skin was more reddish whereas in September, it became more yellowish. 2. As for the value, both in March and in September, the hairline was darkest, and the lightest areas were the jaw and the inner arm which showed a similar value. The group of women who put on make-up had the highest value, whereas the men's group showed the lowest result in value. We suppose it to be due to the fact that Putting on make-up prevented the melanin pigmentation by blocking the UV rays. 3. We could observe the highest value in chrome in the chin area both in March and in September, and there was no significant change. There was a difference in men and women's groups, but not a significant one within the women's groups.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.1-9
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• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.79-86
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• 2009

This study proposed a method of detecting the facial area by calculating Euclidian distances among skin color elements and extracting the characteristics of the face. The proposed algorithm is composed of light calibration and face detection. The light calibration process performs calibration for the change of light. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. From the extracted facial area candidate, the eyes were detected in space C of color model CMY, and the mouth was detected in space Q of color model YIQ. From the extracted facial area candidate, the facial area was detected based on the knowledge of an ordinary face. When an experiment was conducted with 40 color images of face as input images, the method showed a face detection rate of 100%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.455-464
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• 2018

This study investigated whether the whitening effects of fullerene serum occurred through improvement of melanin production and skin tone and evaluated its potential for use as a cosmetic material for adult women aged 30-55 with dull skin color and pigmentation. Subjects were divided into a control group with fullerene-less serum (B) and an experimental group with serum containing 0.1% fullerene (A) and evaluated over 8 weeks. Visual assessment and measurement of skin conditions (melanin index, skin brightness) were conducted before use of and 4 and 8 weeks after use of the product, and a questionnaire survey and safety assessment were conducted at the end of the experiment. The results revealed that the highest decrease was 0.37% in the experimental group (A) after eight weeks of use of the product, but that this difference was not statistically significant. Moreover, no significant differences were observed upon inter-group comparison. Evaluation of changes in the melanin index and inter-group comparison revealed a significant decline in the experimental group (A) at all time points. Additionally, the $L^*$ value (skin brightness) of the experimental group (A) showed a significant increase (improvement) after eight weeks, while in inter-group comparison revealed a significant increase (improvement) at all time points (4 and 8 weeks later) (p<0.05). Based on a questionnaire survey of efficacy, positive response rates such as improvement of the target parts on week 8 were high in terms of 'improvement of skin color.' Moreover, the safety assessment revealed no adverse reactions. In conclusion, serum containing 0.1% fullerene revealed improved melanin production and skin tone (brightness) and confirmed its potential for use as a cosmetic material with brightening efficacy. Taken together, the results of this study indicate systematic investigation of the effective application and cosmetics formulations of this product are warranted.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.67-75
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• 2006

Facial expressions exhibit not only facial feature motions, but also subtle changes in illumination and appearance. Since it is difficult to generate realistic facial expressions by using only geometric deformations, detailed features such as textures should also be deformed to achieve more realistic expression. The existing methods such as the expression ratio image have drawbacks, in that detailed changes of complexion by lighting can not be generated properly. In this paper, we propose a nonlinear model for skin color change and a model-based synthesis method for facial expression that can apply realistic expression details under different lighting conditions. The proposed method is composed of the following three steps; automatic extraction of facial features using active appearance model and geometric deformation of expression using warping, generation of facial expression using a model for nonlinear skin color change, and synthesis of original face with generated expression using a blending ratio that is computed by the Euclidean distance transform. Experimental results show that the proposed method generate realistic facial expressions under various lighting conditions.