• Journal of Sasang Constitutional Medicine
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• v.34 no.4
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• pp.68-80
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• 2022

Objectives This study is to report a significant improvement in a Taeeumin patient with systemic contact dermatitis after eating urushiol chicken by herbal medicine treatment. Methods The patient had complaints of erythema, swelling, pruritus, scaly skin, and facial flushing. We treated the patient with an herbal medicine 'Galgeunhaegi-tang' for three months. We evaluated the treatment outcome of systemic contact dermatitis using the Three Item Severity(TIS) score every visit and facial flushing by Image color summarizer at the first and last visit. Results After the treatment, the severity of the patient's skin complaints lessened from moderate to mild. The Image color summarizer showed a minor decrease in the normalized red color level and a significant increase in the brightness level and facial color percentage. Conclusions The patient diagnosed with systemic contact dermatitis, treated with Galgeunhaegi-tang for three months, showed a significant improvement in skin complaints with brighter and even facial color.

• Journal of Pharmacopuncture
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• v.20 no.2
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• pp.100-106
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• 2017

Objectives: This study aimed to assess a Qi Blood Yin Yang evaluation method systematically and objectively and to identify the correlation between the Qi Blood Yin Yang deficiency pattern (QBYYDP) and facial color. Methods: Thirty-seven participants (17 males, 20 females) were enrolled in this study. Twenty-four (10 males, 14 females) had ages from 40 to over 60, and 13 (7 males and 6 females) were in their twenties. After sufficient rest, facial images were taken with a camera. Based on the results from a questionnaire survey, we divided the participants into five groups: the normal and the Qi-, Blood-, Yin-, and Yang-deficient groups, after which the relationships between the L, 'a', and 'b' values in the Lab color system and the characteristics of the participants in each of the deficient groups were elucidated using a facial color analysis program. Results: The color analysis for Qi-deficient (QD) participants revealed that the L value was fairly decreased in comparison with the normal participants, but the 'a' and 'b' values were almost the same. A comparison between the normal and the Yang-deficient (YaD) groups revealed that the L values were somewhat lower compared to the normal group, but the 'a' and 'b' values were not statistically different. For the Yin-deficient (YiD) group, the L value was slightly lower compared to the normal group, but the 'a' and 'b' values were almost the same and the R values were slightly increased. For the Blood-deficient (BD) group, the L values were slightly increased compared to the normal group, but the 'a' and 'b' values were decreased slightly. Conclusion: This study obtained objective, reliable data for judging the QBYYDP by using facial images and a color analysis program. However, further study with at least 10 or more subjects in each of the deficient groups is necessary to confirm our findings.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.139-142
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• 2001

This paper presents a highly fast and accurate facial region extraction method by using the skin-color-reference map and motion information. First, we construct the robust skin-color-reference map and eliminate the background in image by this map. Additionally, we use the motion information for accurate and fast detection of facial region in image sequences. Then we further apply region growing in the remaining areas with the aid of proposed criteria. The simulation results show the improvement in execution time and accurate detection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.25-30
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• 2008

In this paper, we propose a color quantization method regarding facial image for mobile services. For facial images, skin colors are more emphasized. First, we extract skin-color mask in the image and divide the image into two regions. Next, we extract color pallette for two regions respectively. In the proposed method, the loss in the face region is minimized and it can be useful for mobile services considering facial images. From the 8-bit color quantization experiment, we show that the proposed method works well.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.329-339
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• 2007

In this paper we present a facial region detection algorithm for real-time image with complex background and various illumination using spatial and temporal methods. For Detecting Human region It used summation of Edge-Difference Image between continuous image sequences. Then, Detected facial candidate region is vertically divided two objected. Non facial region is reduced using Analysis of Major Color Component. Non facial region has not available Major Color Component. And then, Background is reduced using boundary information. Finally, The Facial region is detected through horizontal, vertical projection of Images. The experiments show that the proposed algorithm can detect robustly facial region with complex background various illumination images.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.22 no.1
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• pp.19-31
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• 2018

For the purpose of the basic educated-establishment on the diagnostic methods of "facial color and shape which reflect human's spiritual essence and personality", we study on the diagnostic value and application of the human face. The study's domain is divided the form and color of human face. And the form and color of human face is respectively observed the diagnostic value and contents. The form of human face reflect plenty the information of the mankind, and the observation of the face is applied to the "Physiognomie" refering to the external features of humans. Therefore the diagnosis on the form of human face is the primary factor in the grouping of five-element human, the discrimination of the Sasang constitution, and the classification of Hyunsang type. The color of human face reflect the physical information of internal organs and the pathological change of disease, therefore we examine the region, character and grade of disease by the inspection of complexion including the changes of color and luster of the facial skin. The inspection on the color is also the primary factor in the grouping of five-element human, the classification of Hyunsang and the differentiation of syndromes. The value of the inspection of complexion including the changes of color and form of the face is widely known. In the future, we think, we need to study more about the theory of the diagnostic value and application of the human face.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.240-243
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• 2002

In this paper, we propose a face region detection based on skin-color distribution and facial feature extraction algorithm in color still images. To extract face region, we transform color using general skin-color distribution. Facial features are extracted by edge transformation. This detection process reduces calculation time by a scale-down scanning from segmented region. we can detect face region in various facial Expression, skin-color deference and tilted face images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2671-2677
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• 2014

These days, there is increasing those who like spicy food, people release stress by eating spicy food. But, when you eat spicy food, there is a difference but, we visually can be found red facial color to change. In this paper, when you eat spicy food, we carried out experiment which comparison and analysis color change of facial area depending on Sasang constitutional type. To this end, we organized test subject group by Sasang constitutional type according to survey result for Sasang constitutional type. And then we carried out interrelationship analysis between spicy food and facial color depending on facial color to apply Lab color system based on facial image which is before and after eat a hot spicy pepper.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.548-559
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• 2009

The cascade face detector learned by Adaboost algorithm, which was proposed by Viola and Jones, is state of the art face detector due to its great speed and accuracy. In spite of its great performance, it still suffers from false alarms, and more computation is required to reduce them. In this paper, we want to reduce false alarms with less computation using facial color. Using facial color information, proposed face detection model scans sub-window efficiently and adapts a fast face/non-face classifier at the first stage of cascade face detector. This makes face detection faster and reduces false alarms. For facial color filtering, we define a facial color membership function, and facial color filtering image is obtained using that. An integral image is calculated from facial color filtering image. Using this integral image, its density of subwindow could be obtained very fast. The proposed scanning method skips over sub-windows that do not contain possible faces based on this density. And the face/non-face classifier at the first stage of cascade detector rejects a non-face quickly. By experiment, we show that the proposed face detection model reduces false alarms and is faster than the original cascade face detector.