An Empiric Model of Face Detection based on RGB Skin Tone Color
Modern smartphone has been society's lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of those features are face detection. Face detection is the most basic process of any face processing operations. Most digital images are st...
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Published in | Journal of physics. Conference series Vol. 1230; no. 1; pp. 12014 - 12022 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Bristol
IOP Publishing
01.07.2019
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Abstract | Modern smartphone has been society's lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of those features are face detection. Face detection is the most basic process of any face processing operations. Most digital images are stored in the form of RGB (Red, Green, Blue) data. In this research, detection of human face features is done by using different RGB values in digital images. After applying skin tone color segmentation on digital images, detection area will be optimized using human head properties by eliminating non-human face skin tone area. The experiment shows that the detection is mostly accurate for images but there is issue on low light face skin color captured by digital cameras. From the experiment of our model using 10 sample face images, face can be detected on 9 of them, while in 1 image, the face cannot be detected at all because of low light condition. |
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AbstractList | Modern smartphone has been society's lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of those features are face detection. Face detection is the most basic process of any face processing operations. Most digital images are stored in the form of RGB (Red, Green, Blue) data. In this research, detection of human face features is done by using different RGB values in digital images. After applying skin tone color segmentation on digital images, detection area will be optimized using human head properties by eliminating non-human face skin tone area. The experiment shows that the detection is mostly accurate for images but there is issue on low light face skin color captured by digital cameras. From the experiment of our model using 10 sample face images, face can be detected on 9 of them, while in 1 image, the face cannot be detected at all because of low light condition. Abstract Modern smartphone has been society’s lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of those features are face detection. Face detection is the most basic process of any face processing operations. Most digital images are stored in the form of RGB (Red, Green, Blue) data. In this research, detection of human face features is done by using different RGB values in digital images. After applying skin tone color segmentation on digital images, detection area will be optimized using human head properties by eliminating non-human face skin tone area. The experiment shows that the detection is mostly accurate for images but there is issue on low light face skin color captured by digital cameras. From the experiment of our model using 10 sample face images, face can be detected on 9 of them, while in 1 image, the face cannot be detected at all because of low light condition. |
Author | Irviantina, Syanti Ferawaty Jusin Siregar, Saut Dohot Hita Robin Chandra, Wenripin |
Author_xml | – sequence: 1 surname: Robin fullname: Robin email: robin80huang@gmail.com organization: STMIK Mikroskil , Indonesia – sequence: 2 surname: Ferawaty fullname: Ferawaty organization: STMIK Mikroskil , Indonesia – sequence: 3 surname: Jusin fullname: Jusin organization: Universitas Pelita Harapan , Indonesia – sequence: 4 surname: Hita fullname: Hita organization: STMIK Mikroskil , Indonesia – sequence: 5 givenname: Syanti surname: Irviantina fullname: Irviantina, Syanti organization: STMIK Mikroskil , Indonesia – sequence: 6 givenname: Saut Dohot surname: Siregar fullname: Siregar, Saut Dohot organization: Universitas Prima Indonesia , Indonesia – sequence: 7 givenname: Wenripin surname: Chandra fullname: Chandra, Wenripin organization: STMIK Mikroskil , Indonesia |
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Cites_doi | 10.5815/ijigsp.2014.08.06 |
ContentType | Journal Article |
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DOI | 10.1088/1742-6596/1230/1/012014 |
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References | Buza (JPCS_1230_1_012014bib11) 2017 Ghazali (JPCS_1230_1_012014bib3) 2018; 34 Pujol (JPCS_1230_1_012014bib9) 2017 Mohanty (JPCS_1230_1_012014bib8) 2016; 5 Gupta (JPCS_1230_1_012014bib10) 2015; 4 Kumar (JPCS_1230_1_012014bib1) 2014 Kolkul (JPCS_1230_1_012014bib2) 2016 Singh Raghuvanshi (JPCS_1230_1_012014bib6) 2012; 38 Zangana (JPCS_1230_1_012014bib4) 2013; 11 Thakur (JPCS_1230_1_012014bib5) 2011 Aznaveh (JPCS_1230_1_012014bib7) 2009 |
References_xml | – volume: 38 year: 2012 ident: JPCS_1230_1_012014bib6 article-title: Human Face Detection by using Skin Color Segmentation, Face Features and Regions Properties publication-title: International Journal of Computer Applications 0975-8887 contributor: fullname: Singh Raghuvanshi – volume: 5 year: 2016 ident: JPCS_1230_1_012014bib8 publication-title: Skin Color Segmentation based Face Detection using Multi-Color Space IJARCCE contributor: fullname: Mohanty – year: 2009 ident: JPCS_1230_1_012014bib7 contributor: fullname: Aznaveh – year: 2011 ident: JPCS_1230_1_012014bib5 contributor: fullname: Thakur – volume: 4 year: 2015 ident: JPCS_1230_1_012014bib10 publication-title: Enhanced Face Detection Using Skin Color Model:A Review IJARCSEE contributor: fullname: Gupta – year: 2014 ident: JPCS_1230_1_012014bib1 article-title: Real Time Detection and Tracking of Human Face Using Skin Color Segmentation and Region Properties doi: 10.5815/ijigsp.2014.08.06 contributor: fullname: Kumar – volume: 34 year: 2018 ident: JPCS_1230_1_012014bib3 publication-title: An Innovative Face Detection based on Skin Color Segmentation International Journal of Computer Applications contributor: fullname: Ghazali – year: 2017 ident: JPCS_1230_1_012014bib11 contributor: fullname: Buza – year: 2016 ident: JPCS_1230_1_012014bib2 contributor: fullname: Kolkul – volume: 11 year: 2013 ident: JPCS_1230_1_012014bib4 publication-title: A New Algorithm for Human Face Detection Using Skin Color Tone IOSR Journal of Computer Engineering contributor: fullname: Zangana – year: 2017 ident: JPCS_1230_1_012014bib9 contributor: fullname: Pujol |
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Snippet | Modern smartphone has been society's lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of... Abstract Modern smartphone has been society’s lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature.... Modern smartphone has been society’s lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of... |
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SubjectTerms | Color Digital cameras Digital imaging Face recognition Image processing Image segmentation Skin Smartphones |
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Title | An Empiric Model of Face Detection based on RGB Skin Tone Color |
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