• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1044-1056
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• 2013

This paper presents an approach for detecting and measuring human skin pigmentation. In the proposed scheme, we extract a skin area by a GMM-EM clustering based skin color model that is estimated from the statistical analysis of training images and remove tiny noises through the morphology processing. A skin area is decomposed into two components of hemoglobin and melanin by an independent component analysis (ICA) algorithm. Then, we calculate the intensities of hemoglobin and melanin by using the projection transformed block coefficient and determine the existence of skin pigmentation according to the global and local distribution of two intensities. Furthermore, we measure the area and density of the detected skin pigmentation. Experimental results verified that our scheme can both detect the skin pigmentation and measure the quantity of that and also our scheme takes less time because of the location histogram.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.29-36
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• 2012

In this paper, we suggest a new method of detecting human skin-color regions from three-dimensional static or dynamic stereoscopic images by effectively integrating depth and color features. The suggested method first extracts depth information that represents the distance between a camera and an object from input left and right stereoscopic images through a stereo matching technique. It then performs labeling for pixels with similar depth features and determines the labeled regions having human skin color as actual skin color regions. Our experimental results show that the suggested skin region extraction method outperforms existing skin detection methods in terms of skin-color region extraction accuracy.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.27-34
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• 2004

This thesis proposes a face detection algorithm using the color and edge informations in color image. The proposed algorithm segments skin color by Cb and Cr in YCbCr coordinates. Then face candidate regions are made after morphological filtering and labeling. For the regions, the Sobel vortical operation and horizontal projection are performed in the Y luminance components. The peak value indicates the eye location. Similarly, the chin location is detected by the Sobel horizontal operation and horizontal projection. The computer simulation shows that the proposed method gains similar detection rates of previous method and prevent facial region from including neck by detection of chin.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.76-79
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• 2014

Face recognition is very challenging because of the unexpected changes of pose, expression, and illumination. Facial detection in the mobile environments has additional difficulty since the computational resources are very limited. This paper discusses face detection based on frequency domain matched filtering in the mobile environments. Face detection is performed by a linear or phase-only matched filter and sequential verification stages. The candidate window regions are selected by a number of peaks of the matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering tests, which aim to remove false alarms among selected candidate windows. The algorithms are built with JAVA language on the mobile device operated by the Android platform. The simulation and experimental results show that real-time face detection can be performed successfully in the mobile environments.

• Journal of the Korean Applied Science and Technology
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• v.34 no.3
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• pp.595-601
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• 2017

In vivo assay of glucose detection was described using a skin tattoo film electrode (STF), and the probe was made from carbon nano tube paste modification film paper. Here in the square-wave stripping anodic working range obtained of $20-100mgL^{-1}$ within an accumulation time of 0 seconds only in sea water electrolyte solutions of pH 7.0. The relative standard deviations of 50 mg glucose that were observed of 0.14 % (n=12), respectively, using optimum stripping accumulation of 30 sec, the low detection limit (S/N) was pegged at 15.8 mg/L. The developed results can be applied to the detect of in vivo skin sensing in real time. Which confirms the results are usable for in vitro or vivo diagnostic clinical analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.601-603
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• 2004

인터넷은 유익하고 건전한 정보의 유통이 대부분이지만 최근에는 익명성과 상업성으로 인해 유해 정보가 급속하게 늘어나고 있는 추세이다. 이러한 부정적인 영향으로부터 청소년들과 어린이들을 보호하기 위하여, 본 논문은 유해사이트 분류를 자동으로 할 수 있는 시스템을 제안한다. 기존의 유해사이트 구축은 검색 요원들이 유해사이트를 돌아다니며 일일이 데이터를 수집하여 분류하거나 유해사이트의 내용 중에 텍스트만을 추출하여 패턴 매칭 방법으로 분류하는 것이 대부분이었지만, 본 논문은 기존 방법의 문제점을 해결하기 위하여 형태소 분석을 이용한 사이트의 유해도 측정과 Skin-Color 분포의 분석 결과를 병합하여 95% 이상의 정확도(Precision) 성능을 보이며. 신뢰도가 높은 유해사이트 자동 분류 시스템을 구현할 수 있다는 것을 증명하였다.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1203-1211
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• 2022

Melanoma is a skin cancer that starts in pigment-producing cells (melanocytes). The death rates of skin cancer like melanoma can be reduced by early detection and diagnosis of diseases. It is common for doctors to spend a lot of time trying to distinguish between skin lesions and healthy cells because of their striking similarities. The detection of melanoma lesions can be made easier for doctors with the help of an automated classification system that uses deep learning. This study presents a new approach for melanoma classification based on an ensemble of deep convolution neural networks and a Log-Gabor filter. First, we create the Log-Gabor representation of the original image. Then, we input the Log-Gabor representation into a new ensemble of deep convolution neural networks. We evaluated the proposed method on the melanoma dataset collected at Yonsei University and Dongsan Clinic. Based on our numerical results, the proposed framework achieves more accuracy than other approaches.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.351-354
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• 2011

This paper discusses on facial features extraction based on proposed skin color model. Different parts of face from input image are segmented based on skin color model. Moreover, this paper also discusses on concept to detect the eye and mouth position on face. A height and width ratio (${\delta}=1.1618$) based technique is also proposed to accurate detection of face region from the segmented image. Finally, we have cropped the desired part of the face. This exactly exacted face part is useful for face recognition and detection, facial feature analysis and expression analysis. Experimental results of propose method shows that the proposed method is robust and accurate.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.190-192
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• 2006

The clinical characteristics of photodamaged skin, such as coarse and fine wrinkle are not accurately evaluable with previous methods. Public awareness for wrinkle treatment and prevention which rely on proper assessment and evaluation of the underlying skin changes has been increased as the population ages. In this paper, we suggest an in-vivo method and instrument that allow us to acquire a wrinkle-enhanced image to improve the accuracy of quantitative and qualitative analysis for skin wrinkle. The method used involved white LED illumination and photography through polarizing filters. Finally, the polarized light photography yields an accurate and evaluable parameter of photodamaged skin, especially fine and coarse wrinkle.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.609-614
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• 2009

The purpose of this paper is to design the metal object detection system for drive inside protection. To do this, we propose the algorithm for designing the color filter that can detect the metal object using fuzzy theory and the algorithm for detecting area of the driver's face using fuzzy skin color filter. Also, by using the proposed algorithm, we propose the algorithm for detecting the metallic object candidate regions. And, the metallic object color filter is then applied to find the candidate regions. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.