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      KCI등재 SCI SCIE SCOPUS

      Skin Condition Estimation Using Mobile Handheld Camera

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      https://www.riss.kr/link?id=A103376202

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      다국어 초록 (Multilingual Abstract)

      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 i...

      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).

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      참고문헌 (Reference)

      1 이대호, "Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis" 한국전자통신연구원 33 (33): 415-422, 2011

      2 N. Ramesh, "Thresholding Based on Histogram Approximation" 142 (142): 271-279, 1995

      3 P. Gallagher, "Smartphones Get Even Smarter Cameras [Future Visions]" 1 (1): 25-30, 2012

      4 F. Gasparini, "Skin Segmentation Using Multiple Thresholding" 6061 : 1-8, 2006

      5 J. J. De Dios, "Skin Color and Feature-Based Segmentation for Face Localization" 46 (46): 1-6, 2007

      6 M. Zhao, "Skin Color Segmentation Based on Improved 2D Otsu and YCgCr" 1954-1957, 2010

      7 X.N. Zhang, "Skin Color Enhancement Based on Favorite Skin Color in HSV Color Space" 56 (56): 1789-1793, 2010

      8 H.C. Do, "Skin Color Detection through Estimation and Conversion of Illuminant Color under Various Illuminations" 53 (53): 1103-1108, 2007

      9 P.G. Cavalcanti, "Pigmented Skin Lesion Segmentation on Macroscopic Images" 1-7, 2010

      10 A. Renyi, "On Measure of Entropy and Information" 1 : 547-561, 1961

      1 이대호, "Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis" 한국전자통신연구원 33 (33): 415-422, 2011

      2 N. Ramesh, "Thresholding Based on Histogram Approximation" 142 (142): 271-279, 1995

      3 P. Gallagher, "Smartphones Get Even Smarter Cameras [Future Visions]" 1 (1): 25-30, 2012

      4 F. Gasparini, "Skin Segmentation Using Multiple Thresholding" 6061 : 1-8, 2006

      5 J. J. De Dios, "Skin Color and Feature-Based Segmentation for Face Localization" 46 (46): 1-6, 2007

      6 M. Zhao, "Skin Color Segmentation Based on Improved 2D Otsu and YCgCr" 1954-1957, 2010

      7 X.N. Zhang, "Skin Color Enhancement Based on Favorite Skin Color in HSV Color Space" 56 (56): 1789-1793, 2010

      8 H.C. Do, "Skin Color Detection through Estimation and Conversion of Illuminant Color under Various Illuminations" 53 (53): 1103-1108, 2007

      9 P.G. Cavalcanti, "Pigmented Skin Lesion Segmentation on Macroscopic Images" 1-7, 2010

      10 A. Renyi, "On Measure of Entropy and Information" 1 : 547-561, 1961

      11 Shian-Ru Ke, "Human Action Recognition Based on 3D Human Modeling and Cyclic HMMs" 한국전자통신연구원 36 (36): 662-672, 2014

      12 김용국, "Feature Detection and Simplification of 3D Face Data with Facial Expressions" 한국전자통신연구원 34 (34): 791-794, 2012

      13 H. Zhou, "Exemplar-Based Segmentation of Pigmented Skin Lesions from Dermoscopy Images" 225-228, 2010

      14 T. Mendonca, "Comparison of Segmentation Methods for Automatic Diagnosis of Dermoscopy Images" 6572-6575, 2007

      15 P. Ghassemi, "Combination of Stokes Polarized Light Image, Roughness Metrics and Morphological Features for the Detection of Melanoma" 8207 : 2012

      16 U. Lipowezhy, "Automatic Freckles Detection and Retouching" 142-146, 2008

      17 R.W. LeAnder, "Automatic Differentiation of Melanoma and Clark Nevus Skin Lesions" 6514 : 65142V-, 2007

      18 N. Otsu, "A Threshold Selection Method from Gray-Level Histogram" 9 (9): 62-66, 1979

      19 R. Lisano, "A Study into Entropy-Based Thresholding for Image Edge Detection" 38-44, 1995

      20 M. Filho, "A Review of the Quantification and Classification of Pigmented Skin Lesions : from Dedicated to Hand-Held Devices" 39 (39): 1-12, 2015

      21 Z. Ma, "A Review of Algorithms for Medical Segmentation and Their Applications to the Female Pelvic Cavity" 13 (13): 235-246, 2010

      22 Q. Wen, "A Novel Fusion Approach for Segmentating Dermoscopy Image Based on Region Consistency" 267-270, 2013

      23 Z. Ma, "A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model" 20 (20): 615-623, 2015

      24 J.N. Kapur, "A New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram" 29 (29): 273-285, 1985

      25 D.M. Tsai, "A Fast Thresholding Selection Procedure for Multimodal and Unimodal Histograms" 16 (16): 653-666, 1995

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2005-09-27 학술지등록 한글명 : ETRI Journal
      외국어명 : ETRI Journal
      KCI등재
      2003-01-01 평가 SCI 등재 (신규평가) KCI등재
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.78 0.28 0.57
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.47 0.42 0.4 0.06
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