• Title/Summary/Keyword: Skin recognition

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Skin Region Extraction Using Color Information and Skin-Color Model (컬러 정보와 피부색 모델을 이용한 피부 영역 검출)

  • Park, Sung-Wook;Park, Jong-Kwan;Park, Jong-Wook
    • 전자공학회논문지 IE
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    • v.45 no.4
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    • pp.60-67
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    • 2008
  • Skin color is a very important information for an automatic face recognition. In this paper, we proposed a skin region extraction method using color information and skin color model. We use the adaptive lighting compensation technique for improved performance of skin region extraction. Also, using an preprocessing filter, normally large areas of easily distinct non skin pixels, are eliminated from further processing. And we use the modified ST color space, where undesired effects are reduced and the skin color distribution fits better than others color space. Experimental results show that the proposed method has better performance than the conventional methods, and reduces processing time by $35{\sim}40%$ on average.

Extraction Method of Skin Region using Skin Color of Eye Zone in YCbCr Color Space (YCbCr 공간에서 눈 영역의 피부색을 이용한 피부영역 검출 기법)

  • Park, Young-Jae;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.7
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    • pp.520-523
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    • 2009
  • There are many ways to judge whether the input image is adult-image or not. Until now, adult image detection has been examined by the ratio of skin area in full image. In this paper, we propose a method to extract skin region in YCbCr. Skin region shows unique distribution in YCbCr, and we will separate the skin region from background using the distribution. First, we are going to find Eye zone using Eye-Map. Then we will find out the color value for the distribution of skin region using the color of Eye zone. Next, we will find the distribution of the area through the skin region in full-image.

Driver face localization using morphological analysis and multi-layer preceptron as a skin-color model (형태분석과 피부색모델을 다층 퍼셉트론으로 사용한 운전자 얼굴추출 기법)

  • Lee, Jong-Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.6 no.4
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    • pp.249-254
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    • 2013
  • In the area of computer vision, face recognition is being intensively researched. It is generally known that before a face is recognized it must be localized. Skin-color information is an important feature to segment skin-color regions. To extract skin-color regions the skin-color model based on multi-layer perceptron has been proposed. Extracted regions are analyzed to emphasize ellipsoidal regions. The results from this study show good accuracy for our vehicle driver face detection system.

A Study on Dynamic Hand Gesture Recognition Using Neural Networks (신경회로망을 이용한 동적 손 제스처 인식에 관한 연구)

  • 조인석;박진현;최영규
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.1
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    • pp.22-31
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    • 2004
  • This paper deals with the dynamic hand gesture recognition based on computer vision using neural networks. This paper proposes a global search method and a local search method to recognize the hand gesture. The global search recognizes a hand among the hand candidates through the entire image search, and the local search recognizes and tracks only the hand through the block search. Dynamic hand gesture recognition method is based on the skin-color and shape analysis with the invariant moment and direction information. Starting point and ending point of the dynamic hand gesture are obtained from hand shape. Experiments have been conducted for hand extraction, hand recognition and dynamic hand gesture recognition. Experimental results show the validity of the proposed method.

A Study on Hand Region Detection for Kinect-Based Hand Shape Recognition (Kinect 기반 손 모양 인식을 위한 손 영역 검출에 관한 연구)

  • Park, Hanhoon;Choi, Junyeong;Park, Jong-Il;Moon, Kwang-Seok
    • Journal of Broadcast Engineering
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    • v.18 no.3
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    • pp.393-400
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    • 2013
  • Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection 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.

An Empirical Research on Skin Care Application Adoption (피부관리 애플리케이션 수용에 대한 설문조사 연구)

  • Jung, Eun-Young;Noh, Joo-Young;Park, Dong-Kyun
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.4
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    • pp.51-60
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    • 2016
  • Consumers who use mobile applications for their skin care are increasing due to increasing interest in skin care and smart phone use. A survey was conducted to select popular skin care mobile applications to be installed in the smart phone targeting 1,000 men and women in South Korea who are interested in their skin care. Questioned items included skin care awareness and recognition, skin care type, and the intention of using skin health care mobile services. The respondents thought the best skin as 'Flawless skin (52.3%)'. Also, 'Skin trouble' and 'Skin aging' were their major concerns. 47.1% of the respondents used mobile skin care applications, and 56.6% intended to try new mobile skin care services. The results on interesting field of skin care showed significant difference depending on gender, marital status, and annual average household income. Moreover, the results on effort made for skin care showed significant difference depending on age, gender, and marital status. They wanted the functions such as 'Review on cosmetic products by brand (23.8%)', 'Self skincare method (16.8%)', 'Continuous monitoring service (16.2%)', 'Information on cosmetic products (13.4%)'. The result of this study would be reliable as basic material for skincare mobile service area. Further studies could be focused on developing application in accordance with needs and how it should be applied.

Performance Comparison of Skin Color Detection Algorithms by the Changes of Backgrounds (배경의 변화에 따른 피부색상 검출 알고리즘의 성능 비교)

  • Jang, Seok-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.3
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    • pp.27-35
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    • 2010
  • Accurately extracting skin color regions is very important in various areas such as face recognition and tracking, facial expression recognition, adult image identification, health-care, and so forth. In this paper, we evaluate the performances of several skin color detection algorithms in indoor environments by changing the distance between the camera and the object as well as the background colors of the object. The distance is from 60cm to 120cm and the background colors are white, black, orange, pink, and yellow, respectively. The algorithms that we use for the performance evaluation are Peer algorithm, NNYUV, NNHSV, LutYUV, and Kimset algorithm. The experimental results show that NNHSV, NNYUV and LutYUV algorithm are stable, but the other algorithms are somewhat sensitive to the changes of backgrounds. As a result, we expect that the comparative experimental results of this paper will be used very effectively when developing a new skin color extraction algorithm which are very robust to dynamic real environments.

Detection of Face and Facial Features in Complex Background from Color Images (복잡한 배경의 칼라영상에서 Face and Facial Features 검출)

  • 김영구;노진우;고한석
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.69-72
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    • 2002
  • Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.

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A Design of Application using Deep Learning Image Recognition for Identification of Individual Skin Diseases (딥러닝 이미지 인식 기술을 활용한 개인 피부질환 식별용 어플리케이션 설계)

  • Bae, Chang-Hui;Kim, Hyeong-Jun;Cho, Won-Young;Ha, Ok-Kyoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.01a
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    • pp.33-34
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    • 2020
  • 사용자의 피부 관리 및 피부질환을 검사하는 기존의 어플리케이션은 유도 질문에 따른 사용자의 응답을 기반으로 결과를 유추하기 때문에 부정확한 진단 결과를 야기한다. 본 논문에서는 사용자의 미용관련 피부질환 이미지를 바탕으로 딥러닝 이미지 인식 기술 적용하여 건선, 사마귀, 여드름, 한포진을 대상으로 피부 미용질환에 대한 식별 정보를 제공하는 어플리케이션을 제시한다. 또한 이미지 인식률이 높은 ResNet과 SE-ResNet 알고리즘을 적용하여 피부질환 식별 적용 시 효과성을 실험적으로 비교한다.

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