• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.267-275
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• 2021

Skin condition is an important concern in beauty aspect. This study considered a rough skin condition analysis method that beauty industry workers can do through visual observation or skin condition images taken with smartphones. First, studies that combine subjective and objective evaluations were selected among degree papers and academic papers searched by keywords related to 'skin condition' in the Research Information Sharing Service(RISS). Among them, papers that derive correlations with visually verifiable factors were selected. Next, the relationship between factors that match subjective skin condition and objective skin measurement results and factors that can be visually identified on the skin surface was investigated. According to the study, the most suitable factor for matching subjective and objective evaluations was 'oil volume', which is significantly related to 'pore', 'skin texture' and 'erythema', which can be visually checked on the skin surface. It is believed that a rough skin condition analysis will be possible using this.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.137-147
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• 2022

Diagnosis and management of skin condition is a very basic and important function in performing its role for workers in the beauty industry and cosmetics industry. For accurate skin condition diagnosis and management, it is necessary to understand the skin condition and needs of customers. In this paper, we developed SCIS, a big data-based skin care information system that supports skin condition diagnosis and management using social media big data for skin condition diagnosis and management. By using the developed system, it is possible to analyze and extract core information for skin condition diagnosis and management based on text information. The skin care information system SCIS developed in this paper consists of big data collection stage, text preprocessing stage, image preprocessing stage, and text word analysis stage. SCIS collected big data necessary for skin diagnosis and management, and extracted key words and topics from text information through simple frequency analysis, relative frequency analysis, co-occurrence analysis, and correlation analysis of key words. In addition, by analyzing the extracted key words and information and performing various visualization processes such as scatter plot, NetworkX, t-SNE, and clustering, it can be used efficiently in diagnosing and managing skin conditions.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.698-700
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• 2023

최근 들어, 미용 상품을 선택하기 전에 자신의 피부 타입과 상태를 정확히 파악하고 맞춤형 상품을 선택하고자 하는 수요가 증가하고 있다. 이에 따라 피부 상태 측정을 위한 기술적 요소의 중요성이 더욱 두드러지고 있다. 그러나 현재까지 피부 상태 측정을 위한 데이터셋이 한국인을 대상으로 측정한 데이터셋이 없는 실정이다. 본 연구에서는 한국인의 피부 상태를 정밀하게 분석하기 위해 고해상도 디지털 카메라로 촬영된 이미지, 정밀 피부측정 장비를 활용하여 측정한 정밀 값, 그리고 피부과 전문의가 진단한 피부상태 진단 등급 데이트를 통합하여 제공을 한다. 추후 제작한 데이터셋을 활용하여 개인 맞춤형 미용상품 추천과 개발 등 다양한 분야에 활용하고자 한다.

• Proceedings of The Korean Society of Health Promotion Conference
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• 2010.05a
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• pp.149-149
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• 2010

본 연구는 인구사회적 특성, 음주, 스트레스 및 수면이 피부건강에 미치는 영향을 파악하기 위하여 415명을 대상으로 하였으며, 그 결과를 요약하면 다음과 같다. 1. 인구사회적 특성에 따른 피부건강상태는 건성 피부, 지성 피부에서 연령에 따른 유의 한 차이를 보였으며, 결혼상태는 기혼자가 미혼자보다 건성 피부의 점수가 유의하게 높았고, 지성 피부, 민감성 피부, 노화 피부는 통계적으로 유의한 차이가 없었다. 2. 음주자, AUDIT 점수 8점 이상인 문제음주자, 16점 이상인 알코올의존자, 및 CAGE가 1점 이상인 문제음주자에서 피부상태의 하위변수인 지성피부에서 유의하였으며, 민감성 피부는 문제음주자에서만 유의하였다. 3. 스트레스와 피부상태와 지각된 피부건강에 차이가 있는지를 분석한 결과 유의하지 않았다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.958-961
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• 2014

최근 영상 분석을 기반으로 한 서비스 어플리케이션의 공급량이 증가하는 추세이다. 특히, 피부 영상 분석 서비스의 경우 주목할 만한 이슈는 접근의 용이함과 편리성을 갖춘 서비스 어플리케이션의 개발이다. 본 논문에서는 사용자의 피부 상태 진단 서비스를 손쉽게 웹 상으로 제공받을 수 있는 어플리케이션 개발에 주안점을 둔다. 이를 위해 피부 현미경으로 촬영된 이미지에 이진화 및 질감 대비 향상, 노이즈 제거 등의 전처리 과정과 Watershed 알고리즘, 외곽선 검출 등의 과정을 거쳐 수치화된 데이터를 산출한다. 최종적으로 피부 주름, 거칠기, 유분, 톤, 민감성 정보를 검출하며 분석 결과를 사용자에게 보여준다. 분석된 피부 영상 정보를 통해 사용자는 쉽게 자신의 피부 상태를 진단 받을 수 있을 것으로 사료된다.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.211-217
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• 2019

In this study, the change of skin condition was analyzed by skin analysis equipment using scrub cosmetics, and the morphological characteristics of microbead were observed by dermascope and scanning electron microscope. In the dermascope observation, during the process of cleansing, the microbeads attached to the skin existed in close contact with each other or dispersed. The skin after scrubbing was clean and smooth and the fine wrinkles between epidermal keratinocytes were reduced. In the scanning electron microscopic observation, the microbead surface did not have severe bending or rough surface. The skin moisture and oil content were higher than the scrub skin before the scrub, and there was no significant difference in the pH.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.495-496
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• 2018

사람의 피부는 개인마다 상태의 차이가 있으며, 개인의 피부 상태에 따가 피부고민도 다르다. 이에 따라, 일반 소비자들의 화장품 사용에 대한 선호도는 나만의 것, 내 피부에 맞는 화장품, 자세한 카운슬링 순으로 선호도가 나타나고 있다. 민간기관에서도 유전자 검사가 가능해짐으로써 상기와 같이 피부에 대한 유전자 분석도 활성화되고 있는 실정으로, 본 논문에서는 개인의 피부 유형과 유전자 정보를 고려하고 소셜 네트워크에서의 데이터를 수집하여 빅데이터 분석을 통한 맞춤형 추천 서비스를 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.742-749
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• 2021

This study aimed to comparatively analyze changes in skin conditions according to the frequency of sheet mask use among women in their 60s. An experiment was performed for 5 weeks from May 1 to June 3, 2020. A total of 70 women in their 60s, who understood the purposes of this study and agreed to the experiment were selected. All empirical analyses were conducted at a significance level of 5%, and the SPSS WIN 21 program was used to perform statistical analysis. Increased moisture content, decreased coarseness, changes in sebum levels, and decreased pigmentation, were significant effects of sheet mask use for 7days per week. As long as the sheet mask did not irritate the skin, had a positive effects on the skin the more often it was used. These results can help in enhancing the effectiveness of systematic measurement and improvement of skin type. To determine factors affecting skin conditions, it is necessary to investigate and compare factors such as effects of dietary or living habits, genetic influence, and living environments.