• 한국컴퓨터정보학회논문지
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• 제27권9호
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• pp.191-203
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• 2022

화장품 및 뷰티산업에서 고객 맞춤형 제품과 서비스를 제공하는 것은 주요 기술 트렌드이고, 피부상태 진단과 관리는 중요한 필수기능이다. 고객의 요구 수준은 더욱더 높아지고 있으며 이에 대한 다양하고 섬세한 고민과 요구 사항이 소셜미디어 커뮤니티에서 활발하게 다루어지고 있다. 소셜미디어 상의 이미지는 매우 다양하고 비정형적이므로 피부상태 진단 및 관리에 필요한 체계적인 피부 이미지 식별을 위한 시스템이 필요하다. 본 논문에서는 소셜미디어 인스타그램에서 수집한 빅데이터로부터 피부 이미지 데이터를 지능적으로 식별하고, 피부상태 진단 및 관리를 위한 정형화된 피부 샘플 데이터를 추출하는 시스템을 개발하였다. 본 논문에서 제안한 시스템은 빅데이터수집분석단계, 피부이미지분석단계, 훈련데이터준비단계, 인공신경망훈련단계, 피부이미지식별단계로 구성된다. 빅데이터수집분석단계에서는 인스타그램으로부터 빅데이터를 수집하고 피부 상태 진단 및 관리를 위한 이미지 정보를 분석결과로 저장한다. 피부이미지분석단계에서는 전통적인 이미지 처리 기법을 사용하여 피부 이미지의 평가 및 분석 결과를 획득한다. 훈련데이터준비단계에서는 피부이미지 분석결과로부터 피부 샘플데이터를 추출하여 훈련데이터를 준비하였다. 그리고 인공신경망훈련단계에서는 이 훈련데이터를 사용하여 지능적으로 피부 이미지 유형을 예측하는 인공신경망 AnnSampleSkin을 단계별 고도화와 훈련을 통해 모델을 완성하였다. 피부이미지식별단계에서는 소셜미디어로부터 수집된 이미지에 대해 피부샘플을 추출하고, 훈련된 인공신경망 AnnSampleSkin의 이미지 유형 예측 결과들을 통합하여 최종 피부 이미지 유형을 지능적으로 식별한다. 본 논문에서 제안된 피부이미지식별 방법은 약 92% 이상의 높은 피부 이미지 식별 정확도를 나타내고 있고, 정형화된 피부 샘플 이미지 빅데이터를 제공할 수 있게 되었다. 추출된 피부샘플 세트는 피부 상태를 진단하고 관리하는데 매우 효율적이고 유용한 정형화된 피부 이미지 데이터로 사용될 것으로 기대된다.

• ETRI Journal
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• 제38권4호
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• pp.776-786
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• 2016

The fairly recent standard of equipping mobile devices with advanced imaging sensors has opened the possibility of conveniently diagnosing skin conditions, anywhere, anytime. For this application, we attempted to estimate skin conditions from a skin image taken by a mobile handheld camera. To estimate the skin conditions, we specifically identified three skin features (pigmentation, pores, and roughness) that can be measured quantitatively from a skin image. The experimental data indicate that the existing thresholding methods are inappropriate for extracting the pigmentation and pore skin features. Thus, we propose a new line-fitting based thresholding method for skin feature detection. We thoroughly evaluated our proposed skin condition estimation method using our skin image database. The experimental results show that our proposed thresholding method can better determine the threshold leading to the most visually plausible detection, when compared to existing methods. We also confirmed that skin conditions can be feasibly estimated using a common mobile handheld camera (for example, a smartphone).

• 한국실내디자인학회논문집
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• 제17권2호
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• pp.30-38
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• 2008

It has been stated that the outer skin of an architecture should be related to and express the interior programs. It was rather moral issue than practicality. In contemporary urban cities, this nicely-linked relationship between exterior and interior has become much more complex and, in many cases, is no more valid. It tends that contemporary architectural skin is somehow separately developed and has its own logic to be independent from what is inside. This research focuses on these sort of logical design process to make unique image of skin in which conceptual thinking, spatialization and materialization are mixed together. More specifically this study articulates' expandable patternization process' based on the notion that it has a crucial role to systematically construct an image of skin. Expandable patternization has a couple of stages to complete an architectural skin. The first element is a single unit and the second is organization or arrangement of units based on a logical process. Lastly, the third is spatialization after relating the skin to the interior programs as well as environmental surroundings. It is found that, although, in most related projects, the architect or designer has followed his or her own preference or design tendencies, many skin projects has based the given unique characteristics from the beginning. This study concludes that skin design is not just an image making, but has an important role to amalgamate various aspects of an architectural projects: programs, concept of architect, environment, structure as well as image.

• 대한의용생체공학회:의공학회지
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• 제28권2호
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• pp.195-198
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• 2007

In this paper, we introduce a digital cross-polarization and fluorescent color imaging system for quantitative evaluation of skin lesions. We describe the characterization of the imaging systems and the quantitative image analysis methods to show the feasibility for quantitative evaluation of skin lesions. The polarization color image was used to compute erythema and melanin index image which are useful for quantitative evaluation of pigmentation and vascular skin lesions, respectively. The fluorescent color image was used to quantitatively evaluate "sebum" and "vitiligo". In quantitative evaluation of various skin lesions, we confirmed the clinical efficacy of the imaging systems for dermatological applications. Finally, we sure that the imaging systems can be utilized as important assistant tools for the evaluation of skin lesions by providing reproducible quantitative result for widely distributed skin lesions.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권7호
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• pp.520-523
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• 2009

입력된 영상을 유해영상인지 아닌지 판단하기 위해 여러 가지 방법이 사용 될 수 있다. 현재, 대부분의 유해영상검출에 대한 연구는 피부색상이 전체영상에서 차지 하는 비율에 기반하고 있다. 본 논문에서는 YCbCr에서 피부영역을 검출 하는 기법을 제안한다. 피부영역은 YCbCr에서 특정적인 분포를 나타내는데 이를 이용하여 배경영역과 피부영역을 분리하고자 한다. 먼저 Eye-Map을 이용하여 눈의 영역을 찾은 후 그 주변 영역의 색상을 이용해 피부영역의 색상값 분포를 찾고, 전체 영상에서 그 분포와 근거리에 있는 영역들을 피부영역으로 검출하는 방식이 된다.

• 한국정보기술학회 영문논문지
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• 제8권2호
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• pp.47-58
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• 2018

In this paper, we propose a method for skin condition analysis using a camera module embedded in a smartphone without a separate skin diagnosis device. The type of skin disease detected in facial image taken by smartphone is acne, pigmentation, blemish and flush. Face features and regions were detected using Haar features, and skin regions were detected using YCbCr and HSV color models. Acne and flush were extracted by setting the range of a component image hue, and pigmentation was calculated by calculating the factor between the minimum and maximum value of the corresponding skin pixel in the component image R. Blemish was detected on the basis of adaptive thresholds in gray scale level images. As a result of the experiment, the proposed skin condition analysis showed that skin diseases of acne, pigmentation, blemish and flush were effectively detected.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2004년도 Asia Display / IMID 04
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• pp.432-435
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• 2004

The skin color of a human being is the important memory color influencing image quality for color display. Therefore, in this paper, the preferred skin color axis is defined on HSV color space by analyzing some previous research, and the preferred skin color reproduction algorithm is performed by rotating the center axis of skin distribution of an input image to the preferred skin color axis.

• 대한화장품학회지
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• 제16권1호
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• pp.47-63
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• 1990

Image analyser was used to understand the condition of skin surface and to evaluate the efficacy of cosmetic treatment. It was unsatisfactory to analyse skin surface structure although several methods using image analyser had been presented. We developed the new system composed of image analyser and Tandem Scanning Reflected Light Microscope (TSRLM) having the remarkable optical sectioning property as image input device. By using this new system, we quantitatively measured the change of skin surface, the depth and width of furrow in micron unit, resulted by cosmetic treatments. And also three dimensional image of skin was reconstructed with serial sectioned images, which were captured through TSRLM, for better understanding of the effect of cosmetic treatment. It was found that skin relief was more easily understood and the change of skin surface caused by cosmetic treatment was more accurately measured by using this system. In addition, we was also aware of the possibility of in vivo direct measurement of skin furrow without replica. It was conceivable that our system could be applicable for study of cosmetic effects further.

• Journal of Information Processing Systems
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• 제9권1호
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• pp.141-156
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• 2013

In this paper we propose a method to detect human faces in color images. Many existing systems use a window-based classifier that scans the entire image for the presence of the human face and such systems suffers from scale variation, pose variation, illumination changes, etc. Here, we propose a lighting insensitive face detection method based upon the edge and skin tone information of the input color image. First, image enhancement is performed, especially if the image is acquired from an unconstrained illumination condition. Next, skin segmentation in YCbCr and RGB space is conducted. The result of skin segmentation is refined using the skin tone percentage index method. The edges of the input image are combined with the skin tone image to separate all non-face regions from candidate faces. Candidate verification using primitive shape features of the face is applied to decide which of the candidate regions corresponds to a face. The advantage of the proposed method is that it can detect faces that are of different sizes, in different poses, and that are making different expressions under unconstrained illumination conditions.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.193-196
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• 2009

단일 영상에서 피부색 영역을 추출하기 위해서 기존의 많은 방법들이 하나의 고정된 피부색 모델을 사용한다. 그러나 영상에 특성에 따라 영상에 포함된 피부색의 분포가 다양하기 때문에 이러한 방법을 이용하여 피부색을 검출할 경우 낮은 검출율이나 높은 긍정 오류율이 발생할 수 있다. 따라서 영상의 특징에 따라 적응적으로 피부색 영역을 추출할 수 있는 방법이 필요하다. 이에 본 논문에서는 영상의 특징에 따라 2단계의 과정을 거쳐 피부색 모델을 수정하는 방법으로, 다양한 조명과 환경 조건에서 높은 검출율과 낮은 긍정 오류율을 동시에 가지는 알고리즘을 제안한다.