• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.2 no.3
• /
• pp.79-86
• /
• 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 Haehwa Medicine
• /
• v.19 no.1
• /
• pp.87-98
• /
• 2010

There are four kinds of diagnosis methods in oriental medicine, and viewing diagnosis(望診) is the most important method among them. There are two ways in viewing diagnosis. These are viewing shape(觀形) and inspecting color(察色). Viewing shape diagnosis includes observation on geometric curve that is made by prominence of bones or lump of flesh, and examination on symmetric disparity and balance of vertical length among three vertical section of face. Inspecting color is literally inspecting several specified region of face. By Viewing shape, we can learn about characteristic physical mechanism of individuals, and basic disposition of reaction from inside and outside infinite stimulations. On the other hand, by inspecting color, we can estimate the very present pathologic and physiologic status of the patient. the estimation is based on principle that inside body changes reveal some reflections on facial skin surface. When you diagnosis patients with inspecting color method, It is important to distinguish color delicately, and to know where to see and what to know from it. The most important and frequently mentioned regions are myong-dang(明堂), eyes(眼) and In-dang(印堂). Myong-dang(明堂) indicates nose. In-dang(印堂) indicates the space between eyebrows. Unlike myong-dang(印堂) and eyes, In-dang(印堂) is occasionally treated as a trivial region then others. But, from research on classical books of facial examination and consideration of it's locational meanings, we've learned In-dang(印堂) is very important in viewing diagnosis, because this region is crossing of the other two regions and this fact means this region expresses the spiritual status as well as physical status in one region.

• Journal of Korea Multimedia Society
• /
• v.20 no.2
• /
• pp.108-114
• /
• 2017

Lip reading is a field of image processing to assist the process of sound recognition. In some environment, the capture of sound signal usually has significant noise and therefore, the recognition rate of sound signal decreases. Lip reading can be a good feature for the increase of recognition rates. Conventional lip extraction methods have been proposed widely. Maia et. al. proposed a method by the sum of Cr and Cb. However, there are two problems as follows: the point with maximum saturation is not always regarded as lips region and the inner part of lips such as oral cavity and teeth can be classified as lips. To solve these problems, this paper proposes a method which adopts the histogram-based classifier for the extraction of lips region. The proposed method consists of two stages, learning and test. The amount of computation is minimized because this method has no color conversion. The performance of proposed method gives 66.8% of detection rate compared to 28% of conventional ones.

• Journal of Industrial Technology
• /
• v.28 no.B
• /
• pp.143-148
• /
• 2008

A real-time face detection is to find human faces robustly under the cluttered background free from the effect of occlusion by other objects or various lightening conditions. We propose a face detection system for real-time applications using wavelet decomposition method based on Gabor features. Firstly, skin candidate regions are extracted from the given image by skin color filtering and projection method. Then Gabor-feature based template matching is performed to choose face cadidate from the skin candidate regions. The chosen face candidate region is transformed into 2-level wavelet decomposition images, from which feature vectors are extracted for classification. Based on the extracted feature vectors, the face candidate region is finally classified into either face or nonface class by the Levenberg-Marguardt back-propagation neural network.

• Journal of Broadcast Engineering
• /
• v.18 no.3
• /
• pp.393-400
• /
• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.22 no.2
• /
• pp.76-88
• /
• 1996

The facial color is affected by age increase, health condition, internal and/or external environment factors and so on. Especially, the external environment factors in accordance with the influence of environment pollution that is air pollution, exert a bad influence of skin. The object of this study shall be quantified the facial color change in accordance with age increase, external environment factors. Therefore we have make the measurement about the facial color change of Korean women by regional groups. We've quantified through correlation equation, the rate of the many external environment factors which influence the facial color change (air pollution, climate condition, season etc.) As the result of the study, we have reach to know that CO, $O_3$, $NO_2$ has high relation with hue, value, chrome change. The facial color change is proved to be influenced atmospheric environment condition. Besides in hue and value in relation with meteorology demonstrates its link with the temperature, the evaporation quantity, the duration of sunshine of each region. Therefore we have instill cognition of the environmental pollution in accordance with external environment factor that was quantified. And we have reach to know this study affects cosmetics development of new concept.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.7
• /
• pp.821-829
• /
• 2004

A face recognition has been used for verifying and authorizing valid users, but its applications have been restricted according to lighting conditions. In order to minimizing the restricted conditions, this paper proposes a new algorithm of detecting the face from the input image obtained under the irregular lighting condition. First, the proposed algorithm extracts an edge difference image from the input image where a skin color and a face contour are disappeared due to the background color or the lighting direction. In the next step, it extracts a face region using the histogram of the edge difference image and the intensity information. Using the intensity information, the face region is divided into the horizontal regions with feasible facial features. The each of horizontal regions is classified as three groups with the facial features(including eye, nose, and mouth) and the facial features are extracted using empirical properties of the facial features. Only when the facial features satisfy their topological rules, the face region is considered as a face. It has been proved by the experiments that the proposed algorithm can detect faces even when the large portion of face contour is lost due to the inadequate lighting condition or the image background color is similar to the skin color.

• Journal of IKEEE
• /
• v.6 no.1 s.10
• /
• pp.72-79
• /
• 2002

This paper presents an efficient face detection algorithm for color images with a complex background. The presented algorithm utilizes the color information and eigenface that is calculated by PCA-LDA (Principle Component Analysis - Linear Discriminant Analysis). The method of using the color information is faster than any other methods. Eigenface includes average information of the whole test faces. Therefore eigenface can decide that the candidate region is a face. The whole process is composed of two steps. First, it finds first face candidates region of skin tone using a color information in image. We can get a size and position of face candidate region. Second, we compare first face candidate region with eigenface, so decide that an image whether include a face or not. The advantages of the proposed approach include that increasing the detection speed by deciding a size and position of first face candidates region. Also, Betting 97% of the detection rate by comparing the eigenfaces calculated in PCA-LDA.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.39-41
• /
• 2006

It is important to estimate the hand skin temperature because it reveals not only physiological properties of a certain diseases but also it can estimate even human mental-stress conditions. In this study, we try to estimate the temporal skin temperature distribution of human hand by applying stress-cold test to possibly apply to estimate a subject's blood circulation condition in his or her hand in terms of normal or abnormal state.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.664-667
• /
• 2009

There is strong demand to create wearable PC systems that can support the user outdoors. When we are outdoors, our movement makes it impossible to use traditional input devices such as keyboards and mice. We propose a hand gesture interface based on image processing to operate wearable PCs. The semi-transparent PC screen is displayed on the head mount display (HMD), and the user makes hand gestures to select icons on the screen. The user's hand is extracted from the images captured by a color camera mounted above the HMD. Since skin color can vary widely due to outdoor lighting effects, a key problem is accurately discrimination the hand from the background. The proposed method does not assume any fixed skin color space. First, the image is divided into blocks and blocks with similar average color are linked. Contiguous regions are then subjected to hand recognition. Blocks on the edges of the hand region are subdivided for more accurate finger discrimination. A change in hand shape is recognized as hand movement. Our current input interface associates a hand grasp with a mouse click. Tests on a prototype system confirm that the proposed method recognizes hand gestures accurately at high speed. We intend to develop a wider range of recognizable gestures.