Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1946
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dc.contributor.authorSae-Bae, Napa-
dc.contributor.authorSun, Xiaoxi-
dc.contributor.authorSencar, Hüsrev Taha-
dc.contributor.authorMemon, Nasir D.-
dc.date.accessioned2019-07-10T14:42:41Z
dc.date.available2019-07-10T14:42:41Z
dc.date.issued2014
dc.identifier.citationSae-Bae, N., Sun, X., Sencar, H. T., & Memon, N. D. (2014, October). Towards automatic detection of child pornography. In 2014 IEEE International Conference on Image Processing (ICIP)(pp. 5332-5336). IEEE.en_US
dc.identifier.isbn978-1-4799-5751-4
dc.identifier.issn1522-4880
dc.identifier.urihttps://ieeexplore.ieee.org/document/7026079-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/1946-
dc.description.abstractThis paper presents a child pornographic image detection system that identifies human skin tones in digital images, extracts features to detect explicit images and performs facial image based age classification. The novelty of the technique relies on the use of a robust and very fast skin color filter and a new set of facial features for improved identification of child faces. Tests on a dataset containing explicit images taken under different illuminations and reflecting a diversity of human skin tones, show that explicit images can be differentiated from benign images with around 90% accuracy. Similarly, tests performed on adult and child facial images yielded an accuracy of 80% in detecting child faces. Test conducted on 105 images involving semi-naked children (with no sexual context) revealed that the system has true positive rates of 83% in detecting explicit-like images and 96.5% in detecting child faces.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 IEEE International Conference on Image Processingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectImage processingen_US
dc.subjectStatistical testsen_US
dc.subjectAge classificationen_US
dc.subjectAutomatic Detectionen_US
dc.subjectChild pornographiesen_US
dc.subjectDigital imageen_US
dc.subjectFacial featureen_US
dc.subjectImage detection systemsen_US
dc.subjectSkin color filteren_US
dc.subjectTrue positive ratesen_US
dc.titleTowards Automatic Detection of Child Pornographyen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.startpage5332
dc.identifier.endpage5336
dc.authorid0000-0001-6910-6194-
dc.identifier.wosWOS:000370063605100en_US
dc.identifier.scopus2-s2.0-84949928560en_US
dc.institutionauthorSencar, Hüsrev Taha-
dc.identifier.doi10.1109/ICIP.2014.7026079-
dc.authorscopusid8616233200-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusquality--
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.3. Department of Computer Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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