• Archives of Plastic Surgery
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• v.43 no.3
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• pp.225-228
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• 2016

• Fashion & Textile Research Journal
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• v.25 no.2
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• pp.248-254
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• 2023

This study aims to measure the skin rigidity of different facial areas among Koreans and propose guidelines for each area's skin rigidity that can be applied with a facial robot for testing respiratory protective devices. The facial skin rigidity of 40 participants, which included 20 men and 20 women, aged 20 to 50, was analyzed. The rigidity measurement was conducted in 13 facial areas, including six areas in contact with the mask and seven non-contact areas, by referring to the facial measurement guidelines of Size Korea. The facial rigidity was measured using the Durometer RX-1600-OO while in a supine position. The measurement procedure involved contacting the durometer vertically with the reference point, repeating the measurement of the same area five times, and using the average of three values whose variability was between 0.4 and 4.2 Shore OO. The rigidity data analysis used precision analysis, descriptive statistics analysis, and mixed-effect ANOVA. The analysis confirmed the rigidity of the 13 measurement areas, with the highest rigidity of the face being at the nose and forehead points, with values of 51.2 and 50.8, respectively, and the lowest rigidity being at the chin and center of the cheek points, with values of 19.2 and 20.7, respectively. Significant differences between gender groups were observed in four areas: the tip of the nose, the point below the chin, the area below the lower jaw, and the inner concha.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2333-2345
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• 2024

Facial wrinkles are widely used to evaluate skin condition or aging for various fields such as skin diagnosis, plastic surgery consultations, and cosmetic recommendations. In order to effectively process facial wrinkles in facial image analysis, accurate wrinkle segmentation is required to identify wrinkled regions. Existing deep learning-based methods have difficulty segmenting fine wrinkles due to insufficient wrinkle data and the imbalance between wrinkle and non-wrinkle data. Therefore, in this paper, we propose a new facial wrinkle segmentation method based on a UNet++ model. Specifically, we construct a new facial wrinkle dataset by manually annotating fine wrinkles across the entire face. We then extract only the skin region from the facial image using a facial landmark point extractor. Lastly, we train the UNet++ model using both dice loss and focal loss to alleviate the class imbalance problem. To validate the effectiveness of the proposed method, we conduct comprehensive experiments using our facial wrinkle dataset. The experimental results showed that the proposed method was superior to the latest wrinkle segmentation method by 9.77%p and 10.04%p in IoU and F1 score, respectively.

• Fashion & Textile Research Journal
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• v.11 no.1
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• pp.103-111
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• 2009

This study is to help make-up and coordination for image-making after analysis of facial color and shape of elderly women. The data was analyzed 55-75 years old 212 elderly women's face color and pictures by means of SPSS 12.0 statistics package. On the basis of the colorimetric data on face by Minolta CM2500D, this research considered the analysis of facial color, patternization of facial color and its analysis by age group; for the analysis of facial shape, this research patternized facial shape and analyzed its characteristic using both contour-based facial shape analysis and Kamata facial shape analysis. As for facial color, it was found that the lower age bracket has bright and reddish face, looking fine, while the higher age bracket has a conspicuously yellowish face, looking bad. The community of facial color is classified as 3 types and it was found out that the facial color of the subjects belonging to Type 3, whose L value is the largest, looked the brightest; the face of the subjects belonging to Type 2, whose a value is the largest, was much tinged with red, and the face of the subjects belonging to Type 1, whose b value is the largest were tinged with yellow. According to the analysis of facial shape, there appeared oval & long forms in the classification by contour, while there appeared a lot of downward-directed power and inner-directed power in the classification by Kamata, which is believed to reflect the phenomenon that their chin line becomes roundish and the facial length also tend to be longer due to aging.

• Archives of Plastic Surgery
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• v.33 no.4
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• pp.525-529
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• 2006

Purpose: Facial nerve injury is a rare but feared complication of face lift. Uncertainty as to the depth and vulnerability of the facial nerve in face lift dissection causes some surgeon, particularly novices, to dissect slowly. Excessively thin flaps can be made because of fear of nerve injury, contributing to skin slough. Methods: From September 1998 to February 2003, the authors operated on 34 aging face patients using classical face-lift. We had analysed about quantity of skin removal and degree of elevated flap. The authors have found quantity of skin removal was 1.5-2.0 cm, degree of elevated flap was 40-45 degree on average. Results: The authors performed preauricular pre-excision face-lift technique on 12 aging face patients from July 2003 to Feburary 2005 based on experienced surgery. This technique reduced fear of dissecting skin flap necrosis and facial nerve injury because of firmly attached pre-auricular skin removed in advance. Conclusions: We easily dissected SMAS without visual field disturbance, nerve damage and reduced operation time and bleeding loss compared to classical face-lift.

• Archives of Plastic Surgery
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• v.44 no.6
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• pp.559-563
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• 2017

Supported by recent literature on the signs of aging of the middle and lower face, our clinical research has documented a loss of volume of the deep structural components of the central face and a progressive descent of the nasolabial fat and the jowl fat, leading to facial fragmentation. The signs that appear around the age of 45 to 50 years are well targeted by the mini-invasive technique described here. We focused on refitting the jowl fat and the nasolabial fat associated with cutaneous tightening. The use of absorbable barbed sutures (Quill) led to significant improvements, enabling the fitting of fat on fat. In the past 4 years, 167 operations were performed using this technique. The clinical results were very satisfactory, yielding a natural effect caused by the mobilization and strong fixation of the nasolabial fat and the jowl fat in the direction opposite to their displacement.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.101-111
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• 1994

The human face can provide a great deal of information in regard to his/her race, age, sex, personality, feeling, psychology, mental state, health condition and ect. If we pay a close attention to the aging process, we are able to find out that there are recognizable phenomena such as eyelid drooping, cheek drooping, forehead furrowing, hair falling-out, the hair becomes gray and etc. This paper proposes that the method to estimate the age by analyzing these feature components for the facial image. Ang we also introduce the method of facial image synthesis in accordance with the cange of age. The feature components according to the change of age can be obtainec by dividing the facial image into the 3-dimensional shape of a face and the texture of a face and then analyzing the principle component respectively using 3-dimensional model. We assume the age of the facial image by comparing the extracted feature component to the facial image and synthesize the resulted image by adding or subtracting the feature component to/from the facial image. As a resurt of this simulation, we have obtained the age changed ficial image of high quality.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.29 no.2
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• pp.106-111
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• 2016

Objective : The aim of this study is to report the effect of Hani-maehwa laser(fractional mode) treatment on acne scar. Methods : The patient with atrophic facial acne scars was treated with 5 sessions of laser therapy at 4-week intervals. The therapeutic response to treatment was assessed at 3 months after last laser session. The treatment effect was evaluated by standardized photography, anti aging, skin brightness and flatness. That was measured by micro fluorescence measurement camera(ECO SKIN, Cuvitz Inc.) in 16(left zygoma) and 26(right zygoma) spot. And side effects were also checked. Results : Atrophic facial acne scars have improved markedly. Anti aging, skin brightness and flatness were improved. Especially anti aging and flatness were noticeably improved. Adverse effects were not reported.Conclusions : Korean medicine cautery method applies to high level laser(CO₂ Hani-maehwa laser). These are different designs but same principle. It can be considered that laser therapy is effective method for treating acne scars.

• Journal of information and communication convergence engineering
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• v.22 no.3
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• pp.256-266
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• 2024

Sasang constitutional medicine (SCM) is one of the best traditional therapeutic approaches used in Korea. SCM prioritizes personalized treatment that considers the unique constitution of an individual and encompasses their physical characteristics, personality traits, and susceptibility to specific diseases. Facial features are essential for diagnosing Sasang constitutional types (SCTs). This study aimed to develop a real-time artificial intelligence-based model for diagnosing SCTs using facial images, building an SCTs prediction model based on a machine learning method. Facial features from all images were extracted to develop this model using feature engineering and machine learning techniques. The fusion of these features was used to train the AI model. We used four machine learning algorithms, namely, random forest (RF), multilayer perceptron (MLP), gradient boosting machine (GBM), and extreme gradient boosting (XGB), to investigate SCTs. The GBM outperformed all the other models. The highest accuracy achieved in the experiment was 81%, indicating the robustness of the proposed model and suitability for real-time applications.

• Journal of Platform Technology
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• v.11 no.5
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• pp.16-22
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• 2023

There is a growing interest in facial age estimation because many applications require age estimation techniques from facial images. In order to estimate the exact age of a face, a technique for extracting aging features from a face image and classifying the age according to the extracted features is required. Recently, the performance of various CNN-based deep learning models has been greatly improved in the image recognition field, and various CNN-based deep learning models are being used to improve performance in the field of facial age estimation. In this paper, age estimation performance was compared by learning facial features based on various CNN-based models such as AlexNet, VGG-16, VGG-19, ResNet-18, ResNet-34, ResNet-50, ResNet-101, ResNet-152. As a result of experiment, it was confirmed that the performance of the facial age estimation models using ResNet-34 was the best.