• The Journal of the Society of Korean Medicine Diagnostics
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• v.12 no.2
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• pp.49-60
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• 2008

Objectives: The aim of this study was to investigate correlation of the phlegm-retained fluid, namely Damum(痰飮) and dark circles under eyes. Methods: 2 males and 11 females aged 26-60 years were participated in this study. They were asked the intensity of 29 symptoms related with Damum(痰飮) including dark circle with the questionnaire published by the Journal of the Korea Institute of Oriental Medical Diagnostics. Three skin researchers including OMD graded the dark circles by inspection. We took the pictures around eyes by Facial Stage (Moritex, Japan) and analyzed the skin color by Image-Pro Plus (Media Cybernetics, USA). Results: There was statistically significant correlation between Damum(痰飮) and dark circles measured by self, inspectors and image analysis. Conclusions: In the Oriental Medicine, It is reported that the shadows under eyes are the sign of the retention of fluid, Damum(痰飮). In our study, that shadows, namely dark circles, has correlation with the symptoms of Damum(痰飮). Especially, the correlation between inspected grade and image analysis was very high. According to the above results, it is proved that dark circles under eyes are important diagnostic sign of Damum(痰飮).

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.77-82
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• 2012

We carried out study to prove effectiveness as stimulating corresponding points to lung in hand to experiment applied analysis parameters for image and audio signals in this paper. To this end we collected facial image and voice before and after stimulating corresponding points to lung in hand to a male 20s 25 people. In addition, we analyzed change color, voice energy and speaking rate of right cheek area corresponding points to lung to suggest the theory of the Oriental medicine diagnosis based on data collected. As a result, after performing hand acupuncture, L value of right cheek area decreased average 2.33 and a value b value increased 0.76, 0.97 on average. In addition, size of voice energy increased average 0.42, speaking rate decreased average 0.07. In other words, effect of lung function was improved using hand acupuncture corresponding points to lung.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.121-123
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• 2006

얼굴의 표정은 얼굴의 구성요소 같은 기하학적 정보와 조명이나 주름 같은 세부적인 정보들로 표현된다. 얼굴 표정은 기하학적 변형만으로는 실감적인 표정을 생성하기 힘들기 때문에 기하학적 변형과 더불어 텍스쳐 같은 세부적인 정보도 함께 변형해야만 실감적인 표현을 할 수 있다. 표정비율이미지 (Expression Ratio Image)같은 얼굴 텍스처의 세부적인 정보를 변형하기 위한 기존 방법들은 조명에 따른 피부색의 변화를 정확히 표현할 수 없는 단점이 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 서로 다른 조명 조건에서도 실감적인 표정 텍스처 정보를 적용할 수 있는 비선형 피부색 모델 기반의 표정 합성 방법을 제안한다. 제안된 방법은 동적 외양 모델을 이용한 자동적인 얼굴 특징 추출과 와핑을 통한 표정 변형 단계, 비선형 피부색 변화 모델을 이용한 표정 생성 단계, Euclidean Distance Transform (EDT)에 의해 계산된 혼합 비율을 사용한 원본 얼굴 영상과 생성된 표정의 합성 등 총 3 단계로 구성된다. 실험결과는 제안된 방법이 다양한 조명조건에서도 자연스럽고 실감적인 표정을 표현한다는 것을 보인다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.

• Korean Journal of Oriental Medicine
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• v.14 no.3
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• pp.89-95
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• 2008

A tongue shows physiological and clinicopathological changes of inner organs. Visual inspection of a tongue is not only convenient but also non-invasive. To develop an automat ic tongue diagnosis system for an objective and standardized diagnosis, the separation of the tongue are a from a facial image and the detection of coatings, spots and cracks are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth as well as those of tongue furs and body are similar. The propose d method includes preprocessing with down-sampling and edge enhancement, over-segmentation, detecting positions with a local minimum over shading from the structure of a tongue, and correcting local minima or detecting edge with color difference. The proposed method produces the region of a segmented tongue, and then decomposes the color components of the region into hue, saturation and brightness, resulting in classifying the regions of tongue furs(coatings) into kinds of coatings and substance and segmenting them. Spots are detected by using local maxima and the variation of saturation, and cracks are searched by using local minima and the directivity of dark areas in brightness. The results illustrate the segmented region with effective information, excluding a non-tongue region and also give us accurate discrimination of coatings and the precise detection of spots and cracks. It can be used to make an objective and standardized diagnosis for an u-Healthcare system as well as a home care system.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.2812-2818
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• 2013

Medicine such as Korean oriental medicine and alternative medicine is inferior to western medicine in diagnostic skills and treatment regimen but despite going through a lot of in western medicine preference to that is situations. Likewise, in Korean oriental medicine and alternative medicine have been closely linked to that effect not proven scientifically to be solved is regarded as the biggest drawback. In this paper, auricular therapy that is often used in alternative medicine to help strengthen the internal organs function which whether the conduct of stimulating ear is effective or not by applying to ocular inspection of Korean oriental medicine is proposed. For this purpose, lung ear reflex points to stimulate were performed after the right cheek color by measuring stimulation before comparison and analysis of the experiments. In addition, in order to examine this first analysis of the human body to the lungs and the elements of image analysis is to study. Experimental result, derived b value increased to a value of the right cheek and the results by lung ear to stimulate reflex point.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.299-308
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• 2009

AAM(Active Appearance Model) is an algorithm to extract face feature points with statistical models of shape and texture information based on PCA(Principal Component Analysis). This method is widely used for face recognition, face modeling and expression recognition. However, the detection performance of AAM algorithm is sensitive to initial value and the AAM method has the problem that detection error is increased when an input image is quite different from training data. Especially, the algorithm shows high accuracy in case of closed lips but the detection error is increased in case of opened lips and deformed lips according to the facial expression of user. To solve these problems, we propose the improved AAM algorithm using lip feature points which is extracted based on a new lip detection algorithm. In this paper, we select a searching region based on the face feature points which are detected by AAM algorithm. And lip corner points are extracted by using Canny edge detection and histogram projection method in the selected searching region. Then, lip region is accurately detected by combining color and edge information of lip in the searching region which is adjusted based on the position of the detected lip corners. Based on that, the accuracy and processing speed of lip detection are improved. Experimental results showed that the RMS(Root Mean Square) error of the proposed method was reduced as much as 4.21 pixels compared to that only using AAM algorithm.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.437-446
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• 2012

A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.178-187
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• 2018

This study aimed to develop a model of the program for automation measuring the preference of the portraits based on the relationship between the image quality factors and the preferences in the portraits for manufacturers aiming at high utilization of the users. in order to proceed with the evaluation, the image quality measurement was divided into objective and subjective items, and the evaluation was done through image processing and statistical methods. the image quality measurement items can be divided into objective evaluation items and subjective evaluation items. RSC Contrast, Dynamic Range and Noise were selected for the objective evaluation items, and the numerical values were statistically analyzed and evaluated through the program. Exposure, Color Tone, composition of person, position of person, and out of focus were selected for subjective evaluation items and evaluated by image processing method. By applying objective and subjective assessment items, the results were very accurate, with the results obtained by the developed program and the results of the actual visual inspection. but since the currently developed program can be evalua ted only after facial recognition of the person, future research will need to develop a program that can evaluate all kinds of portraits.