• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.19-30
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• 2009

In this paper, We propose a method with which we can detect facial components and face in input image. We use eye map and mouth map to detect facial components using eyes and mouth. First, We find out eye zone, and second, We find out color value distribution of skin region using the color around the eye zone. Skin region have characteristic distribution in YCbCr color space. By using it, we separate the skin region and background area. We find out the color value distribution of the extracted skin region and extract around the region. Then, detect mouth using mouthmap from extracted skin region. Proposed method is better than traditional method the reason for it comes good result with accurate mouth region.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.39-47
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• 2010

A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.56-63
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• 2007

In this paper, an eye tracking method is presented using a neural network (NN) and mean-shift algorithm that can accurately detect and track user's eyes under the cluttered background. In the proposed method, to deal with the rigid head motion, the facial region is first obtained using skin-color model and con-nected-component analysis. Thereafter the eye regions are localized using neural network (NN)-based tex-ture classifier that discriminates the facial region into eye class and non-eye class, which enables our method to accurately detect users' eyes even if they put on glasses. Once the eye region is localized, they are continuously and correctly tracking by mean-shift algorithm. To assess the validity of the proposed method, it is applied to the interface system using eye movement and is tested with a group of 25 users through playing a 'aligns games.' The results show that the system process more than 30 frames/sec on PC for the $320{\times}240$ size input image and supply a user-friendly and convenient access to a computer in real-time operation.

• Journal of Life Science
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• v.28 no.3
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• pp.331-338
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• 2018

Melanin is a polymer substance that plays an important role in the determination of hair growth and skin color in vivo. However, melanin, which is over-produced by reactive oxygen species, is known to cause stains, freckles, and hypercholesterolemia, which are associated with aging. Previous studies have shown that polyphosphate, one of the components of Rhynchosia Nulubilis, inhibits skin aging induced by ultraviolet rays. The aim of this study is to investigate the direct effect of Rhynchosia Nulubilis ethanolic extract (RNEE) on melanin synthesis. In this study, RNEE showed no antioxidative effects on scavenging activity of DPPH radical in addition to reducing power. The cytotoxicity of RNEE was increased in a dose-dependent manner in an MTT assay. In addition, RNEE increased tyrosinase activity and melanin synthesis in DOPA-oxidation experiments. RNEE did not promote the conversion L-DOPA into melanin in live cells, but melanin production was promoted in the RNEE-treated group after H2O2 pretreatment compared to the control group in which melanin production was reduced by treatment with H2O2. In addition, RNEE increased the expression level of tyrosinase related protein-2 (TRP-2) and increased the expression level of tyrosinase related protein-1 (TRP-1) at a concentration of $16{\mu}g/ml$. In particular, it was found that RNEE increased the expression level of SOD-3, by which superoxide anion is converted to hydrogen peroxide, higher than the control and ${\alpha}$-MSH used as a positive control at a concentration of more than $16{\mu}g/ml$. The results suggest that RNEE can induce melanogenesis related to black hair.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.123-131
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• 2008

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of one's health like the physiological and the clinicopathological changes of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition a lot. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue region from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmenting, detecting the edge with a local minimum over a shading area from the structure of a tongue, correcting local minima or detecting the edge with the greatest color difference, selecting one edge to correspond to a tongue shape, and smoothing edges, where preprocessing consists of down-sampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue. Finally, the systematic procedure separated only a tongue region from a face image with a tongue, which was obtained from a digital tongue diagnosis system. Oriental medical doctors' evaluation for the results illustrated that the segmented region excluding a non-tongue region provides important information for the accurate diagnosis. The proposed method can be used for an objective and standardized diagnosis and for an u-Healthcare system.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1196-1204
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• 2012

In this paper, a series of algorithms are proposed for controlling different kinds of multimedia contents and realizing interact between human and computer by using single input device. Human gesture recognition based on NUI is presented firstly in my paper. Since the image information we get it from camera is not sensitive for further processing, we transform it to YCbCr color space, and then morphological processing algorithm is used to delete unuseful noise. Boundary Energy and depth information is extracted for hand detection. After we receive the image of hand detection, PCA algorithm is used to recognize hand posture, difference image and moment method are used to detect hand centroid and extract trajectory of hand movement. 8 direction codes are defined for quantifying gesture trajectory, so the symbol value will be affirmed. Furthermore, HMM algorithm is used for hand gesture recognition based on the symbol value. According to series of methods we presented, we can control multimedia contents by using human gesture recognition. Through large numbers of experiments, the algorithms we presented have satisfying performance, hand detection rate is up to 94.25%, gesture recognition rate exceed 92.6%, hand posture recognition rate can achieve 85.86%, and face detection rate is up to 89.58%. According to these experiment results, we can control many kinds of multimedia contents on computer effectively, such as video player, MP3, e-book and so on.

• Journal of Genetic Medicine
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• v.4 no.1
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• pp.38-44
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• 2007

Purpose : Menkes disease is an X-linked recessively inherited disorder caused by the mutation of the ATP7A gene encoding copper-transporting P-type AT Pase. The phenotypic features are progressive neurological degeneration, mental retardation, loose skin, and vascular complications. Early diagnosis and treatment are very important for the prognosis of Menkes disease. Here, we describe nov el mutations of the ATP7A gene and prenatal diagnosis by mutation analysis. Methods : Five unrelated Korean Menkes patients were included in this study. They presented with depigmented wool-like hair, progressive neurologic deterioration, and hypotonia in infancy. Serum copper and ceruloplasmin levels w ere decreased. Brain magnetic resonance imaging revealed tortuous intracranial vessels. Mutation analysis has been carried out using cDNA from cultured skin fibroblasts or genomic DNA from peripheral leukocytes. Prenatal diagnosis was performed in two cases using chorionic villi samples or amniocytes. Results : Four novel mutations have been identified from four different families; c.3511+1G>A (p.E1099_N1171delinsMfsX 18), c.4005+5 G>A (p.V1268_R1335del), c.1870_2172del (p.S624_Q724del), and c.3352 G>A (p.G1118S). T he remaining one was previously reported (c.1933 C>T (p.V 1268_R1335del)). On prenatal DNA analysis, one w as diagnosed as normal, while the other turned out to be a female heterozygote with p.S624_Q724del mutation of the ATP7A gene. Conclusion : We identified 4 novel mutations of the ATP7A gene. Prenatal diagnosis in families at risk is critical in order to choose preventiv e options including an early treatment with copper-histidine therapy or therapeutic termination. Most mutations of the ATP7A gene were frame-shift mutations and prenatal diagnosis has been successfully carried out.