• Title/Summary/Keyword: 피부검출

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Skin Region Detection Using Histogram Approximation Based Mean Shift Algorithm (Mean Shift 알고리즘 기반의 히스토그램 근사화를 이용한 피부 영역 검출)

  • Byun, Ki-Won;Joo, Jae-Heum;Nam, Ki-Gon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.21-29
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    • 2011
  • At existing skin detection methods using skin color information defined based on the prior knowldege, threshold value to be used at the stage of dividing the backround and the skin region was decided on a subjective point of view through experiments. Also, threshold value was selected in a passive manner according to their background and illumination environments in these existing methods. These existing methods displayed a drawback in that their performance was fully influenced by the threshold value estimated through repetitive experiments. To overcome the drawback of existing methods, this paper propose a skin region detection method using a histogram approximation based on the mean shift algorithm. The proposed method is to divide the background region and the skin region by using the mean shift method at the histogram of the skin-map of the input image generated by the comparison of the similarity with the standard skin color at the CbCr color space and actively finding the maximum value converged by brightness level. Since the histogram has a form of discontinuous function accumulated according to the brightness value of the pixel, it gets approximated as a Gaussian Mixture Model (GMM) using the Bezier Curve method. Thus, the proposed method detects the skin region by using the mean shift method and actively finding the maximum value which eventually becomes the dividing point, not by using the manually selected threshold value unlike other existing methods. This method detects the skin region high performance effectively through experiments.

Face Detection for Intelligent Video Conference System (지능형 영상회의를 위한 얼굴검출)

  • Park, Jae-Hyeon;Park, Gyu-Sik;On, Seung-Yeop;Kim, Cheon-Guk
    • The KIPS Transactions:PartB
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    • v.8B no.1
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    • pp.20-27
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    • 2001
  • 얼굴검출은 현재 많은 연구가 활발히 진행되고 있는 분야로 보안, 인식 등 다양한 응용분야를 갖는다. 본 논문은 카메라가 화자의 이동에 따라 이를 추적하여 회전하고 회의상황에 맞는 앵글을 유지하는 지능형 영상회의 시스템 개발의 기본요소인 화자검출의 선행단계로 얼굴검출에 대한 새로운 방법을 제안한다. RGB 색 공간의 입력영상을 YIQ 공간으로 변환한 후 IQ 성분은 피부영역검출에 Y 성분은 얼굴의 특성을 추출하는데 사용된다. 색 분포도를 이용하여 피부영역을 검출하고, 마스크를 누적 적용하여 잡음을 제거한 후 얼굴의 구조적인 특성과 명암의 분포를 이용하여 얼굴영역이 검출된다. 실험결과 다양한 배경의 영상에서 여러 명의 얼굴이 오류 없이 검출됨이 관찰되었다.

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Moving Face Detection using Color and Motion Information (칼라와 움직임 정보를 이용한 움직이는 얼굴 영역 검출 방법)

  • 이연철;김은이;박상용;황상원;김항준
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.379-381
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    • 2001
  • 본 논문은 카메라의 움직임이 있는 영상에서 움직이는 사람의 얼굴을 검출하는 방법을 제안한다. 제안된 방법에서, 얼굴 영역을 찾기 위해 피부 색깔 정보와 움직임 정보를 이용한다. 카메라의 움직임을 어파인 모션 모델(Affine Motion Model)을 이용해 제거한 후, 적응적 임계치(adaptive thresholding)를 통해 얻어진 움직임 영역 내에서만 피부 색깔 모델(skin color model)을 이용해 얼굴 영역을 검출한다. 제안된 방법은 시간에 따라 조명이 변하거나 잡음이 포함된 영상에서도 좋은 결과를 얻을 수 있다.

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Skin segmentation and hand tracking for gesture recognition (제스처 인식을 위한 피부영역 분할기법 및 추적)

  • Chae, Seung-Ho;Seo, Jong-Hoon;Han, Tack-Don
    • Proceedings of the Korea Multimedia Society Conference
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    • 2012.05a
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    • pp.371-373
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    • 2012
  • 본 논문에서는 컬러 영상 기반에서 배경에 강인한 피부 영역 검출 기법을 제안하고 손 인식기법을 활용한 응용프로그램을 제안한다. 코드북 모델[1]을 이용하여 배경/전경을 분리하고, 분리된 전경에서 피부색정보를 이용하여 관심영역을 도출한다. 피부 영역을 검출하기 위한 단계에서는 YCbCr, HSV, LUV 색상 모델의 혼합하여 피부색 후보 영역에 대한 임계구간을 통해 강인한 피부 영역을 분할한다. 분할된 영역을 관심영역으로 설정하고 Kalman filter를 이용하여 영역을 추적한다. 결과적으로 복잡하고 고정된 배경에서 조명에 강인한 피부 영역 분할 및 추적이 가능하며 이를 응용한 사용자 인터페이스로 사용될 수 있다.

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Robust Skin Area Detection Method in Color Distorted Images (색 왜곡 영상에서의 강건한 피부영역 탐지 방법)

  • Hwang, Daedong;Lee, Keunsoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.7
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    • pp.350-356
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    • 2017
  • With increasing attention to real-time body detection, active research is being conducted on human body detection based on skin color. Despite this, most existing skin detection methods utilize static skin color models and have detection rates in images, in which colors are distorted. This study proposed a method of detecting the skin region using a fuzzy classification of the gradient map, saturation, and Cb and Cr in the YCbCr space. The proposed method, first, creates a gradient map, followed by a saturation map, CbCR map, fuzzy classification, and skin region binarization in that order. The focus of this method is to rigorously detect human skin regardless of the lighting, race, age, and individual differences, using features other than color. On the other hand,the borders between these features and non-skin regions are unclear. To solve this problem, the membership functions were defined by analyzing the relationship between the gradient, saturation, and color features and generate 108 fuzzy rules. The detection accuracy of the proposed method was 86.35%, which is 2~5% better than the conventional method.

Memory-Free Skin-Detection Algorithm and Implementation of Hardware Design for Small-Sized Display Device (소형 DISPLAY 장치를 위한 비 메모리 피부 검출 알고리즘 및 HARDWARE 구현)

  • Im, Jeong-Uk;Song, Jin-Gun;Ha, Joo-Young;Kang, Bong-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.8
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    • pp.1456-1464
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    • 2007
  • The research of skin-tone detection has been conducting continuously to enlarge the importance in security, surveillance and administration of the information and 'Password Control System' for using face and skin recognition in airports, harbors and general companies. As well as tile rapid diffusion of the application range in image communications and an electron transaction using wide range of communication network, the importance of the accurate detection of skin color has been augmenting recently. In this paper, it will set up the boundaries of skin colors using the information of Cb and Cr in YCbCr color model of human skin color which is from hundreds compiled portrait images for each race, and suggest a efficient yet simple structure about the skin detection which has been followed by whether the comprehension of the boundaries of skin or not with adaptive skin-range set. With the possibility of the 1D Processes which does not use any memory, it is able to be applied to relatively small-sized hardware and system such as mobile apparatuses. To add the selective mode, it is not only available the improvement of tie skin detection, but also showing the correspondent results about previous face recognition technologies using complicated algorithm.

Extracting skin roughness from dermoscopy images for skin age estimation (피부 나이 측정을 위한 피부 현미경 영상에서의 피부 거칠기 추출)

  • Rew, Jehyeok;Suk, Jangmi;Hwang, Eenjun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.815-818
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    • 2014
  • 영상 분석을 통한 특징 추출은 객체의 인식이나 매칭, 인덱싱 등을 위해 수반되는 준비 단계로서 분야별로 다양한 방식을 통해 수행되어 왔다. 특히, 피부 영상 분석에 있어 주목할 만한 이슈는 피부의 노화 정도를 측정하는 것이다. 피부의 거칠기는 피부의 상태와 노화를 판단하는 중요한 근거의 하나이다. 본 논문에서는 피부 나이를 측정하기 위해 피부 현미경 영상에서 피부 거칠기를 평가하는 방법을 제안한다. 이를 위해 피부 현미경으로 촬영된 이미지에 이진화 및 질감 대비 향상, 노이즈 제거 등의 전처리 과정을 수행하고, Watershed 알고리즘과 외곽선 검출을 통해, 피부를 구성하는 셀들의 영역 정보를 획득한다. 이를 바탕으로 피부 거침의 변화량을 계산하여 거칠기를 정의한다. 제안한 방법의 효과를 검증하기 위해 다양한 연령대의 피험자로부터 피부 현미경 영상을 확보하고 실험을 통해 피부 거칠기 특징이 피험자의 연령대와 상관관계가 있음을 보인다.

Face Detection and Tracking using Skin Color Information and Haar-Like Features in Real-Time Video (실시간 영상에서 피부색상 정보와 Haar-Like Feature를 이용한 얼굴 검출 및 추적)

  • Kim, Dong-Hyeon;Im, Jae-Hyun;Kim, Dae-Hee;Kim, Tae-Kyung;Paik, Joon-Ki
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.146-149
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    • 2009
  • Face detection and recognition in real-time video constitutes one of the recent topics in the field of computer vision. In this paper, we propose face detection and tracking algorithm using the skin color and haar-like feature in real-time video sequence. The proposed algorithm further includes color space to enhance the result using haar-like feature and skin color. Experiment results reveal the real-time video processing speed and improvement in the rate of tracking.

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A Study on Adaptive Skin Extraction using a Gradient Map and Saturation Features (경사도 맵과 채도 특징을 이용한 적응적 피부영역 검출에 관한 연구)

  • Hwang, Dae-Dong;Lee, Keun-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.7
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    • pp.4508-4515
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    • 2014
  • Real-time body detection has been researched actively. On the other hand, the detection rate of color distorted images is low because most existing detection methods use static skin color model. Therefore, this paper proposes a new method for detecting the skin color region using a gradient map and saturation features. The basic procedure of the proposed method sequentially consists of creating a gradient map, extracting a gradient feature of skin regions, noise removal using the saturation features of skin, creating a cluster for extraction regions, detecting skin regions using cluster information, and verifying the results. This method uses features other than the color to strengthen skin detection not affected by light, race, age, individual features, etc. The results of the detection rate showed that the proposed method is 10% or more higher than the traditional methods.

A Distribution of Keratinophilic Fungi Isolated from the Soil of Haeundae Beach in Korea (부산 해운대 백사장에서 분리한 각질친화성 피부사상균의 분포)

  • Kim, Sojin;Kim, Su Jung
    • Korean Journal of Clinical Laboratory Science
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    • v.48 no.4
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    • pp.343-347
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    • 2016
  • Keratinophilic fungus (KPF), a type of dermatophytes, is usually present as normal flora on the skin of humans and animals but can produce ring worm-like dermatophytosis by invading the skin in infected individuals. They are distributed worldwide, but their occurrences vary distinctively in accordance with the geographical location and environmental change. Because these fungi grow by degrading keratin, they are abundantly found on the skin, hair, and nails, which are rich in keratin. To investigate the presence of keratinophilic fungi in the soil, we selected a popular beach in South Korea, Haeundae Beach, where numerous people gather each year during the summer holidays. Hundred soil samples were analyzed using the hair-baiting technique, among which, a total of 23 colonies of KPF were identified from 21 soil samples. The identified KPF were Microsporum gypseum (43%), Chrysosporium spp. (35%), Trichophyton ajelloi (13%), and Microsporum cookie (9%). This study confirmed that pathogenic fungi can be found in places crowded by many people. Further research and continuous data collection are needed to confirm the distribution of pathogenic KPF.