Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6797
Title: Hair and Bare Skin Discrimination for Laser-Assisted Hair Removal Systems
Authors: Çayır, Sercan
Yetik, İmam Şamil
Keywords: Laser-Assisted Hair Removal
image processing
automated hair localization
Publisher: IEEE
Source: 39th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) -- JUL 11-15, 2017 -- SOUTH KOREA
Series/Report no.: PROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY
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 %).
URI: https://hdl.handle.net/20.500.11851/6797
ISBN: 978-1-5090-2809-2
ISSN: 1094-687X
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

Show full item record



CORE Recommender

Page view(s)

16
checked on Apr 15, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.