Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/6797
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Çayır, Sercan | - |
dc.contributor.author | Yetik, İmam Şamil | - |
dc.date.accessioned | 2021-09-11T15:43:37Z | - |
dc.date.available | 2021-09-11T15:43:37Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.citation | 39th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) -- JUL 11-15, 2017 -- SOUTH KOREA | en_US |
dc.identifier.isbn | 978-1-5090-2809-2 | - |
dc.identifier.issn | 1094-687X | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/6797 | - |
dc.description.abstract | Laser-assisted hair removal devices aim to remove body hair permanently. In most cases, these devices irradiate the whole area of the skin with a homogenous power density. Thus, a significant portion of the skin, where hair is not present, is burnt unnecessarily causing health risks. Therefore, methods that can distinguish hair regions automatically would be very helpful avoiding these unnecessary applications of laser. This study proposes a new system of algorithms to detect hair regions with the help of a digital camera. Unlike previous limited number of studies, our methods are very fast allowing for real-time application. Proposed methods are based on certain features derived from histograms of hair and skin regions. We compare our algorithm with competing methods in terms of localization performance and computation time and show that a much faster real-time accurate localization of hair regions is possible with the proposed method. Our results show that the algorithm we have developed is extremely fast (around 45 milliseconds) allowing for real-time application with high accuracy hair localization (96.48 %). | en_US |
dc.description.sponsorship | IEEE Engn Med & Biol Soc, PubMed, MEDLINE, Korean Soc Med & Biol Engn | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartof | 2017 39Th Annual International Conference of The IEEE Engineering In Medicine And Biology Society (Embc) | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Laser-Assisted Hair Removal | en_US |
dc.subject | image processing | en_US |
dc.subject | automated hair localization | en_US |
dc.title | Hair and Bare Skin Discrimination for Laser-Assisted Hair Removal Systems | en_US |
dc.type | Conference Object | en_US |
dc.relation.ispartofseries | PROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Electrical and Electronics Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü | tr_TR |
dc.identifier.startpage | 604 | en_US |
dc.identifier.endpage | 607 | en_US |
dc.authorid | 0000-0002-7330-4692 | - |
dc.identifier.wos | WOS:000427085301017 | en_US |
dc.identifier.scopus | 2-s2.0-85032188397 | en_US |
dc.institutionauthor | Yetik, Imam Şamil | - |
dc.identifier.pmid | 29059945 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.relation.conference | 39th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) | en_US |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.5. Department of Electrical and Electronics Engineering | - |
Appears in Collections: | Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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