• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.806-817
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• 2014

The extraction of lip region is essential to Lip Reading, which is a field of image processing to get some meaningful information by the analysis of lip movement from human face image. Many conventional methods to extract lip region are proposed. One is getting the position of lip by using geometric face structure. The other discriminates lip and skin regions by using color information only. The former is more complex than the latter, however it can analyze black and white image also. The latter is very simple compared to the former, however it is very difficult to discriminate lip and skin regions because of close similarity between these two regions. And also, the accuracy is relatively low compared to the former. Conventional analysis of color coordinate systems are mostly based on specific extraction scheme for lip regions rather than coordinate system itself. In this paper, the method for selection of effective color coordinate system and chromaticity transformation to discriminate these two lip and skin region are proposed.

• International Journal of Contents
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• v.9 no.3
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• pp.9-14
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• 2013

In this paper, we will examine single face tracking algorithms with scaling function in a mobile device. Face detection and tracking either in PC or mobile device with scaling function is an unsolved problem. Standard single face tracking method with particle filter has a problem in tracking the objects where the object can move closer or farther from the camera. Therefore, we create an algorithm which can work in a mobile device and perform a scaling function. The key idea of our proposed method is to extract the average of skin color in face detection, then we compare the skin color distribution between the detected face and the tracking face. This method works well if the face position is located in front of the camera. However, this method will not work if the camera moves closer from the initial point of detection. Apart from our weakness of algorithm, we can improve the accuracy of tracking.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5257-5264
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• 2016

Background: Though people of color (POC) are less likely to become afflicted with skin cancer, they are much more likely to die from it due to delay in detection or presentation. Very often, skin cancer is diagnosed at a more advanced stage in POC, making treatment difficult.The purpose of this research was to improve awareness regarding skin cancers in people of color by providing recommendations to clinicians and the general public for early detection and photo protection preventive measures. Methods: Data on different types of skin cancers were presented to POC. Due to limited research, there are few resources providing insights for evaluating darkly pigmented lesions in POC. Diagnostic features for different types of skin cancers were recorded and various possible risk factors were considered. Results: This study provided directions for the prevention and early detection of skin cancer in POC based on a comprehensive review of available data. Conclusions: The increased morbidity and mortality rate associated with skin cancer in POC is due to lack of awareness, diagnosis at a more advanced stage and socioeconomic barriers hindering access to care. Raising public health concerns for skin cancer prevention strategies for all people, regardless of ethnic background and socioeconomic status, is the key to timely diagnosis and treatment.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.105-107
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• 2004

In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on size, angle, and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value(255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking parameters.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.4 s.152
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• pp.567-581
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• 2006

The purpose of this research is to provide the basic data for the development of make-up color application system, based of Korean's skin tone and the preference in make-up color to enhance the effectiveness of the education of beauty in universities. The research was conducted by the previous studies, the analyses of sale's rate of hue-cosmetics, the analytic experiment of color of cosmetics by using Spectrum Color Analyzer and other experimental researches. This research, based on the results of three preliminary researches, shows the result of evaluation from perceivers which has been come out from the experiment of having one model in her twenties being changed with twenty-two different conditions of make-up. Here follows the result of the research. Firstly, there was difference on perceiving images in terms of the gender of perceivers and especially male-group tend to have clearly perceived the gap between elegance-greyish purple, orange-natural, red-classic on monochrome make-up and contrast make-up. Secondly, in terms of lip-colors, salmon pink and pink was regarded positively to both female and male subjects and to male subjects, greyish purple was thought to be better on darker skin-tone and to female subjects, better on lighter skin-tone. Thirdly, on image make-up, romantic gives intelligent image regardless of skin-tone and gender, especially gives more positive looks to male subjects. Natural and classic elements were perceived more positively on darker skin-tone and had bigger perceiving gap in female subjects. Fourthly, in preference rate, male subjects normally preferred the look with make-up than female subjects did and salmon pink and pink lip color was preferred on the darker skin-tone.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.617-618
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• 2011

Everyone's favorite color that exists naturally or artificially. This paper proposes that ow to find a suitable color for man. First of all, we find out about the base tone forming the color such as skin color, hair color, eye color. Next, we explained color theory of four seasons that color was divided according to skin color, hair color, eye color was diveded by spring, summer, autumn and winter seasons, and according to liking or nature. And look at the characteristics of each season's color.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.69-78
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• 2002

This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.35-44
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• 2010

In this paper, we propose a method about producing skin color model adaptively in input image and face detection. The principle process which we proposed is finding eyes candidates by applying the eye features to neural network, and then using the around color to find the distribution of color value. There will be a verification process that producing face region by using color value distribution which is detected as skin region and find mouth candidate in corresponding face region; if eye candidate and mouth candidate's connection structure is similar with face structure, then it can be judged as a face. Because this method can detect skin region adaptively by finding eyes, we solve the rate of false positive about the distorted skin color which is used by existing face detection methods. The experiment was performed about detecting the eye, the skin, the mouth and the face individually. The results revealed that the proposed technique is better than the traditional techniques.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1414-1419
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• 2015

A method for detecting a skin region on the image is generally used to detect the color information. However, If saturation lowered, skin detection is difficult because hue information of the pixels is lost. So in this paper, we propose a method of correcting color of lower saturation of skin region images by the lighting. Color correction process of this method is saturation image acquisition and low-saturation region classification, segmentation, and the saturation of the split in the low saturation region extraction and color values, the color correction sequence. This method extracts the low saturation regions in the image and extract the color and saturation in the region and the surrounding region to produce a color similar to the original color. Therefore, the method of extracting the low saturation region should be correctly preceding. Because more accurate segmentation in the process of obtaining a low saturation regions, we use a multi-threshold method proposed Otsu in Hue values of the HSV color space, and create a binary image. Our experimental results for 170 portrait images show a possibility that the proposed method could be used efficiently preprocessing of skin color detection method, because the detection result of proposed method is 5.8% higher than not used it.