• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.216-221
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• 2003

Emotions recognition is a topic on which little research has been done to date. This paper proposes a new method that can recognize the human s emotion from facial image by using eigenspace. To do so, first, we get the face image by using the skin color from the original color image acquired by CCD color camera. Second, we get the vector image which is projected the obtained face image into eigenspace. And then, we propose the method for finding out each person s identification and emotion from the weight of vector image. Finally, we show the practical application possibility of the proposed method through the experiment.

• Journal of Korea Game Society
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• v.12 no.6
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• pp.121-130
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• 2012

Due to recent developments in smart media, the desire for interaction between humans and computers has increased. In order to satisfy these needs, gesture recognition fields have been actively studied using image processing. In this paper, we propose a method to recognize Chinese hand numeric representation using image processing. The method binarizes an input image based on skin color to extract region of interest and check the number using the angular information of stretched fingers. Our proposed method has 95.83% of recognition rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.447-450
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• 2013

This paper proposes the way to prevent drowsy driving by recognizing drivers eyes and yawn using a front camera. The method uses the Viola-Jones algorithm to detect eyes area and mouth area from detection face region. In the eyes area, it uses the Hough transform to recognize eye circle in order to distinguish drowsy driving. In the mouth area, it determines whether for the driver to yawn through a sub-window testing by applying a HSV-filter and detecting skin color of the tongue. The test result shows that the recognition rate of yawn reaches up to 90%. It is expected that the method introduced in this paper might contribute to reduce the number of drowsy driving accidents.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.319-326
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• 2009

In this paper, we present an algorithm which recognize hand shape in real time using only image without adhering separate sensor. Hand recognizes using edge orientation histogram, which comes under a constant quantity of 2D appearances because hand shape is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantity, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis(PCA) method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Human interface system manufacture technique, which controls a home electric appliance or game using, suggested method at experience could be applied.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.76-79
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• 2014

Face recognition is very challenging because of the unexpected changes of pose, expression, and illumination. Facial detection in the mobile environments has additional difficulty since the computational resources are very limited. This paper discusses face detection based on frequency domain matched filtering in the mobile environments. Face detection is performed by a linear or phase-only matched filter and sequential verification stages. The candidate window regions are selected by a number of peaks of the matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering tests, which aim to remove false alarms among selected candidate windows. The algorithms are built with JAVA language on the mobile device operated by the Android platform. The simulation and experimental results show that real-time face detection can be performed successfully in the mobile environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.403-406
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• 2009

In this paper, we propose a method for deciding permission from the ATM(Automated Teller Machine) using face detection. First, we extract skin areas and make candidate face images from an input image, and then detect a face using Adaboost(Adaptive Boosting) algorithm. Next, proposed method executes a template matching for making a decision on whether to wear accessories like sunglasses or a mask in detected face image. Finally, this method decides whether to permit ATM service using this result. Experimental results show that proposed method performed well at indoors ATM environment for detecting whether to wear accessories.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.34 no.2
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• pp.137-142
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• 2008

Echinacea purpurea, an indian traditional plant medicine has been widely used as herbal remedy for the treatment of disease such as colds or other infections. However, Echinacea purpurea extracts recently have been applied as a cosmetic ingredient for skin care. We artificially cultured Echinacea purpurea by using the bioreactor culture system for this study. We induced callus from Echinacea purpurea and separated adventitious roots, harvested and extracted after cultured in bioreactors. Previously, several studies have been reported on anti-oxidant and immuno-enhancing effects of Echinacea purpurea extract but other efficacies were not well known. In this study, we investigated the whitening, anti-wrinkle and anti-oxidant effects to know applicable value of tissue-cultured Echinacea purpurea adventitious roots extract(TCEPARE) as a cosmetic ingredient. TCEPARE did not show cytotoxicity until a concentration of 2% and showed the anti-oxidative effect in DPPH and NBT tests. Also, the extract decreased tyrosinase expression in a dose-dependent manner and inhibited melanin synthesis in B16 melanoma cells. TCEPARE reduced protein levels of MMP-1, 2 secreted in culture medium or in cell lysates. From these results we suggest that TCEPARE has potential benefits applicable as to cosmetic ingredient for skin care products.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.563-572
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• 2006

Advantage that light transmission treatment way of most suitable through skin can investigate light directly in part ar there is difference in ability photoelectricity month by diverse complexion of horn character department which is branch or head of a family outside part of skin and treatment according to various patient can be inappropriate. By result that this research uses color information after search each color ingredient that ingredient of HIS and YIQ that use method, color information to use skin impedance way and color information through skin area ion and difference video to do fixed measuring by light investigation way by skin impedance corresponds to skin color in an experiment though is most universal result according to patient's skin model area detection each single person's skin model through videotex automatically create and because measuring, investigate skin color, energy, wave length, approximately, transmission time, model of most suitable that draw pulse delay and so on and want and special quality, and saved standard of disease treatment pulse modeling by skin impedance, and design and manufacture light investigation pulse modeling system of most suitable by skin subordinate, and constructed suitable treatment pulse database by skin color.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.145-154
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• 2008

In this paper, we propose the pet robot control system using hand gesture recognition in image sequences acquired from a camera affixed to the pet robot. The proposed system consists of 4 steps; hand detection, feature extraction, gesture recognition and robot control. The hand region is first detected from the input images using the skin color model in HSI color space and connected component analysis. Next, the hand shape and motion features from the image sequences are extracted. Then we consider the hand shape for classification of meaning gestures. Thereafter the hand gesture is recognized by using HMMs (hidden markov models) which have the input as the quantized symbol sequence by the hand motion. Finally the pet robot is controlled by a order corresponding to the recognized hand gesture. We defined four commands of sit down, stand up, lie flat and shake hands for control of pet robot. And we show that user is able to control of pet robot through proposed system in the experiment.