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Skin Condition Estimation Using Mobile Handheld Camera

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dc.contributor.authorBae, Ji-Sang-
dc.contributor.authorJeon, Jae-Ho-
dc.contributor.authorLee, Jae-Young-
dc.contributor.authorKim, Jong-Ok-
dc.date.accessioned2021-09-03T21:31:22Z-
dc.date.available2021-09-03T21:31:22Z-
dc.date.created2021-06-18-
dc.date.issued2016-08-
dc.identifier.issn1225-6463-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/87957-
dc.description.abstractThe 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).-
dc.languageEnglish-
dc.language.isoen-
dc.publisherWILEY-
dc.subjectACTION RECOGNITION-
dc.subjectCOLOR-
dc.titleSkin Condition Estimation Using Mobile Handheld Camera-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Jong-Ok-
dc.identifier.doi10.4218/etrij.16.0115.0942-
dc.identifier.scopusid2-s2.0-84983509006-
dc.identifier.wosid000380802700019-
dc.identifier.bibliographicCitationETRI JOURNAL, v.38, no.4, pp.776 - 786-
dc.relation.isPartOfETRI JOURNAL-
dc.citation.titleETRI JOURNAL-
dc.citation.volume38-
dc.citation.number4-
dc.citation.startPage776-
dc.citation.endPage786-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.identifier.kciidART002130539-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordPlusACTION RECOGNITION-
dc.subject.keywordPlusCOLOR-
dc.subject.keywordAuthorSkin image-
dc.subject.keywordAuthorSegmentation-
dc.subject.keywordAuthorLine-fitting-
dc.subject.keywordAuthorPigmentation-
dc.subject.keywordAuthorPore-
dc.subject.keywordAuthorSkin roughness-
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