• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.1-12
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• 2009

The correct detection of skin color is an important preliminary process in fields of face detection and human motion analysis. It is generally performed by three steps: transforming the pixel color to a non-RGB color space, dropping the illuminance component of skin color, and classifying the pixels by the skin color distribution model. Skin detection depends on by various factors such as color space, presence of the illumination, skin modeling method. In this paper we propose a 3d skin color model that can segment pixels with several ethnic skin color from images with various illumination condition and complicated backgrounds. This proposed skin color model are formed with each components(Y, Cb, Cr) which transform pixel color to YCbCr color space. In order to segment the skin color of several ethnic groups together, we first create the skin color model of each ethnic group, and then merge the skin color model using its skin color probability. Further, proposed model makes several steps of skin color areas that can help to classify proper skin color areas using small training data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.10-15
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• 2012

In a color image, people and especially facial patterns are important and interesting visual objects. Thus, effective skin color reproduction is essential, as skin color is a key memory color in color application systems. Previous studies suggested skin color reproduction by mapping only to the center value of preferred skin region. However, it is not suitable to determine one preference color because preference color from the observer's preference test is not dominant. In this paper, skin color reproduction using multiple preferred skin colors for each race is proposed. The proposed method first defines multiple preferred skin colors for each race according to their luminance level. After that, skin region is detected in an image. The race is then selected by calculating distance between average chromaticity of detected region and that of each racial skin from a database to assign preferred skin color for each race. Next, each corresponding preferred skin color is determined for each selected race. Finally, input skin color is proportionally mapped toward preferred skin color according to the difference between the input skin color and the preferred skin color for a smoothly reproduced skin color. In the experimental results, the proposed method gives better color correction on the objective and subjective evaluation than the previous methods.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.433-435
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• 2001

얼굴 인식분야에서 실시간 얼굴검출에 대한 관심이 높아짐에 따라 피부색컬러 모델을 통한 얼굴영역검출에 대한 연구가 활발히 진행되고 있다. 그러나, 기존의 피부색 모델은 밝기 정보를 제거한 단일 채널의 색상모델이 대부분이다. 이에 본 논문에서는 얼굴피부색을 보다 효과적으로 모델링하기 위하여, 피부색 특성을 고려하여, 밝기 성분을 제거한 RGB 컬러를 모두 사용하는 H, Cb, Cg의 다채널 피부색 모델을 제시한다. 또한, 색상정보에서 사용하지 않은 밝기 정보는 영상 분할을 통해 사용한다. 제안하는 피부색 모델을 통한 얼굴영역 추출 과정을 보인다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.6-7
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• 2011

본 논문에서는 지역적 학습 방법을 활용하는 Average Neighborhood Margin Maximization(ANMM)에 기반하여 피부색과 비피부색 영역을 분리하는 이진 분류의 통계적 접근법을 제안한다. Fisher Linear Discriminant(FLD)와 Average Neighborhood Margin Maximization(ANMM)의 피부색과 비피부색 클래스 내 분산 대비 클래스 간 분산의 비교를 통해 두 클래스 간 분리력 변화를 확인한다. 교사(Supervised) 이진 분류문제에 대하여 Small sample size(SSS) 문제, 가우시안 분포 가정의 문제, 최대 추출 가능 특징 수 제한 문제 등을 해결함과 동시에, 지역적 특성 학습 방법의 도입을 통해 피부색과 비피부색 간 분리력을 향상시킨다.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.54-61
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• 2009

This paper proposes a skin segmentation method based on region histograms of the color quantization map. First, we make a quantization map of the image using the JSEG algorithm and detect the skin pixel. For the skin region detection, the similar neighboring regions are set by its similarity of the size and location between the previous frame and the present frame from the each region of the color quantization map. Then we compare the similarity of histogram between the color distributions of each quantized region and the skin color model using the histogram distance. We select the skin region by the threshold value calculated automatically. The skin model is updated by the skin color information from the selected result. The proposed algorithm was compared with previous algorithms on the ECHO database and the continuous images captured under time varying illumination for adaptation test. Our approach shows better performance than previous approaches on skin color segmentation and adaptation to varying illumination.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1809-1818
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• 2010

In order to detect the skin color area from input images, many prior researches have divided an image into the pixels having a skin color and the other pixels. In a still image or videos, it is very difficult to exactly extract the skin pixels because lighting condition and makeup generate a various variations of skin color. In this thesis, we propose a method that improves its performance using hierarchical merging of 3D skin color model and context informations for the images having various difficulties. We first make 3D color histogram distributions using skin color pixels from many YCbCr color images and then divide the color space into 3 layers including skin color region(Skin), non-skin color region(Non-skin), skin color candidate region (Skinness). When we segment the skin color region from an image, skin color pixel and non-skin color pixels are determined to skin region and non-skin region respectively. If a pixel is belong to Skinness color region, the pixels are divided into skin region or non-skin region according to the context information of its neighbors. Our proposed method can help to efficiently segment the skin color regions from images having many distorted skin colors and similar skin colors.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.193-196
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• 2009

Most of studies adopt a fixed skin color model to segment skin color region in a single image. The methods, however, result in low detection rates or high false positive error rates since the distribution of skin color is varies depending on the characteristics of input image. For the effective skin color segmentation, therefore, we need a adaptive skin color model which changes the model depending on the color distribution of input image. In this paper, we propose a novel adaptive skin color segmentation algorithm consisting of 2 stages which results in both high detection rate and low false positive error rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.112-118
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• 2009

Skin color segmentation techniques have been widely utilized for face/hand detection and tracking in many applications such as a diagnosis system using facial information, human-robot interaction, an image retrieval system. In case of a video image, it is common that the skin color model for a target is updated every frame for the robust target tracking against illumination change. As for a single image, however, most of studies employ a fixed skin color model which may result in low detection rate or high false positive errors. In this paper, we propose a novel method for effective skin color segmentation in a single image, which modifies the conditions for skin color segmentation iteratively by the image feedback of segmented skin color region in a given image.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.297-298
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• 2016

본 논문에서는 손을 보다 효과적으로 인식하기 위해 동작 검출과 피부색 검출을 이용하여 인식하는 시스템을 제안한다. 단순히 피부색만을 이용하여 손을 인식하는 경우 피부색과 유사한 색상의 물체나 다른 신체 부위를 인식하는 문제점이 발생하게 된다. 이러한 문제점을 해결하기 위해 동작 검출을 이용하여 움직이는 물체만을 손이라고 가정하였다. 이렇게 가정을 하고 피부색 검출과 동작 검출을 이용하여 인식하는 경우 신체부위를 제외하고는 거의 검출되지 않는다. 그리고 인식된 영역마다 뼈대를 찾아 손을 검출한다. 조명이나 주변 환경에 최대한 영향을 적게 받기위해 시스템을 설계하였으며 단순 피부색 검출을 이용한 손 검출보다 좋은 성능을 발휘하며 손가락의 개수와 손 모양, 손 추적까지 응용할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.369-372
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• 2007

한의학적 진단 이론은 우수성을 보유하고 있음에도 불구하고 계량화, 정량화되어 시각적으로 표현해 주는 결과를 보이지 못해 서양의학에 비해 뒤떨어져 있는 실정이다. 따라서 본 논문에서는 한의학의 망진을 의료 시스템화 하기 위한 한 단계로서 찰색의 기본이 되는 피부색의 분석을 행하였다. 이를 위해 각 개인의 피부색 차이를 수렴하고 이에 대한 분석을 시행함으로 피부색에 대한 공학적 분석을 시도하였다. 본 논문에서는 객관적으로 피부가 검은 사람과 흰 사람을 비교, 분석하였으며 또한 일반인들을 대상으로 피부색 분석을 실행하여 피부색에 대한 개념을 정립하고자 한다. 마지막으로 이에 대한 평균값을 구하며 망진 시스템의 주된 대상이 되는 황인종의 피부색에 대한 연구를 행하고자 한다.