• 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 Information Technology Services
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• v.6 no.3
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• pp.241-249
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• 2007

This paper describes a real-time face tracking system using effective detector and Kalman filter. In the proposed system, an image is separated into a background and an object using a real-time updated face color for effective face detection. The face features are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted using Principal Component Analysis (PCA), and interpreted principal components are used for Support Vector Machine (SVM) that classifies the faces and non-faces. The moving face is traced with Kalman filter, which uses the static information of the detected faces and the dynamic information of changes between previous and current frames. The proposed system sets up an initial skin color and updates a region of a skin color through a moving skin color in a real time. It is possible to remove a background which has a similar color with a skin through updating a skin color in a real time. Also, as reducing a potential-face region using a skin color, the performance is increased up to 50% when comparing to the case of extracting features from a whole region.

• Journal of the Korean Graphic Arts Communication Society
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• v.16 no.3
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• pp.97-108
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• 1998

Spectral reflectance of the object should be measured to predict the color of object under various illuminants. The spectral reflectance can be represented in a multi-dimension space. Generally the information of inputed image by digital camera and color scanner is represented with 3-dimension color signals such as RGB. In other to predict the color of inputed image under any illuminant, we should be estimated spectral reflectance of the object. In this paper, we described the method to predict spectral reflectance by einenvector using the skin color of printed image, confirmed availability and propriety through experiment. we estimated spectral reflectance of skin color taken by RGB color signals and than reproduced skin color according to various illuminants on CRT.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.4-162
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• 2001

This paper presents a fuzzy-based method for classification skin color object in a complex background under varying illumination Parameters of fuzzy rule base are generated using a genetic algorithm(GA). The color model is used in the YCbCr color space. We propose a unique fuzzy system in order to accommodate varying background color and illumination condition This fuzzy system approach to skin color classification is discussed along with an overview of YCbCr color space.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.

• 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.

• Journal of Korean Physical Therapy Science
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• v.21 no.1
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• pp.37-43
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• 2014

Background : The purpose of this study is to verify the type of influence on the skin color according to the photoaging symptoms depending on the degree of external activities among the factors that influence the skin due to UV exposure and to obtain the basic study data on the physical therapy of the skin. Methods : In this study, in order to investigate the type of influence on the skin color according to the photoaging symptoms when the body is exposed to the UV rays having various effects on our body, a study was conducted using questionnaires and skin color measurement tool targeting 20 male college soccer students with many external activities and the senior high school students who has relatively less external activities due to the preparation for college entrance. The skin color was measured and the results were compared. Result : In the test group having relatively higher external activities, while they had less use of the sunscreen, they had more degree of UV exposure, and for the recognition of ultraviolet hazard, more were aware that it was harmful. In addition, in the skin color measurement test conducted targeting the son and the father in order to investigate the association between the skin color and the genetic factors, the experimental group showed a significant difference(p<.05) but the control group did not show any significant difference(p>.05). Conclusion : Based on such study results, the UV exposure time and the use of sunscreen are thought to be an important factor in the skin care.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.31-38
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• 2011

Skin color is a very important information for an automatic face recognition. In this paper, we proposed a skin region extraction method using the MLP(Multi-Layer Perceptron) and skin color model. We use the adaptive lighting compensation technique for improved performance of skin region extraction. Also, using an preprocessing filter, normally large areas of easily distinct non-skin pixels, are eliminated from further processing. Experimental results show that the proposed method has better performance than the conventional methods, and reduces processing time by 31~49% on average.

• Archives of Plastic Surgery
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• v.35 no.1
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• pp.36-41
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• 2008

Purpose: For facial reconstruction, skin color match is crucial to achieve great aesthetic result. Forehead flap and full thickness skin graft have been used for many years to reconstruct facial defect. Their results are aesthetically valuable with remarkable resemblance and harmony of the skin color between donor and recipient sites. The purpose of this study is to evaluate and compare the aesthetic outcome of the two methods as the analysis of skin color match. Methods: From January 1995 to December 2005, ten forehead flaps and ten full thickness skin grafts were performed. The reconstructed areas of forehead flaps were five noses and five eyelids. Recipient sites of full thickness skin grafts were seven eyelids, two noses and one forehead. In order to obtain the objective validity, the skin color of flap(or graft) and the recipient sites were measured by chromameter. The skin colors were quantified according to a three-dimensional coordinate system used in chromameter, L*(brightness), a*(redness), and b*(yellowness).Results: There was no significant color difference between forehead flap site and adjacent skin in all color values. On the other hand, the L* and b* values of graft sites were significantly lower than those of the adjacent skins. The a* values of graft sites were higher than those of the adjacent skins. Conclusion: This study reveals that skin color match of forehead flap is greater than that of full thickness skin graft. As forehead flap has adequate volume and great color match, it can be useful to reconstruct deep facial defect such as nasal defect. On the other hand, full thickness skin graft can be used for superficial defect like partial eyelid defect.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.641-648
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• 2001

A face detection in color images is important for many multimedia applications. It is first step for face recognition and can be used for classifying specific shorts. This paper describes a new method to detect faces in color images based on the skin color and hair color. This paper presents a fuzzy-based method for classifying skin color region in a complex background under varying illumination. The Fuzzy rule bases of the fuzzy system are generated using training method like a genetic algorithm(GA). We find the skin color region and hair color region using the fuzzy system and apply the convex-hull to each region and find the face from their intersection relationship. To validity the effectiveness of the proposed method, we make experiment with various cases.