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Conference Paper: Source camera identification using footprints from lens aberration

TitleSource camera identification using footprints from lens aberration
Authors
KeywordsForensic science
Image processing
Lens aberration
Source camera identification
Statistical classification
Issue Date2006
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml
Citation
Proceedings Of Spie - The International Society For Optical Engineering, 2006, v. 6069 How to Cite?
AbstractSource camera identification is the process of discerning which camera has been used to capture a particular image. In this paper, we consider the more fundamental problem of trying to classify images captured by a limited number of camera models. Inspired by the previous work that uses sensor imperfection, we propose to use the intrinsic lens aberration as features in the classification. In particular, we focus on lens radial distortion as the primary distinctive feature. For each image under investigation, parameters from pixel intensities and aberration measurements are obtained. We then employ a classifier to identify the source camera of an image. Simulation is carried out to evaluate the success rate of our method. The results show that this is a viable procedure in source camera identification with a high probability of accuracy. Comparing with the procedures using only image intensities, our approach improves the accuracy from 87% to 91%. © 2006 SPIE-IS&T.
Persistent Identifierhttp://hdl.handle.net/10722/99555
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChoi, KSen_HK
dc.contributor.authorLam, EYen_HK
dc.contributor.authorWong, KKYen_HK
dc.date.accessioned2010-09-25T18:35:11Z-
dc.date.available2010-09-25T18:35:11Z-
dc.date.issued2006en_HK
dc.identifier.citationProceedings Of Spie - The International Society For Optical Engineering, 2006, v. 6069en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/99555-
dc.description.abstractSource camera identification is the process of discerning which camera has been used to capture a particular image. In this paper, we consider the more fundamental problem of trying to classify images captured by a limited number of camera models. Inspired by the previous work that uses sensor imperfection, we propose to use the intrinsic lens aberration as features in the classification. In particular, we focus on lens radial distortion as the primary distinctive feature. For each image under investigation, parameters from pixel intensities and aberration measurements are obtained. We then employ a classifier to identify the source camera of an image. Simulation is carried out to evaluate the success rate of our method. The results show that this is a viable procedure in source camera identification with a high probability of accuracy. Comparing with the procedures using only image intensities, our approach improves the accuracy from 87% to 91%. © 2006 SPIE-IS&T.en_HK
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xmlen_HK
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineeringen_HK
dc.subjectForensic scienceen_HK
dc.subjectImage processingen_HK
dc.subjectLens aberrationen_HK
dc.subjectSource camera identificationen_HK
dc.subjectStatistical classificationen_HK
dc.titleSource camera identification using footprints from lens aberrationen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLam, EY:elam@eee.hku.hken_HK
dc.identifier.emailWong, KKY:kywong@eee.hku.hken_HK
dc.identifier.authorityLam, EY=rp00131en_HK
dc.identifier.authorityWong, KKY=rp00189en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1117/12.649775en_HK
dc.identifier.scopuseid_2-s2.0-33645696767en_HK
dc.identifier.hkuros116323en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33645696767&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6069en_HK
dc.identifier.spage155en_HK
dc.identifier.epage162en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChoi, KS=12804359900en_HK
dc.identifier.scopusauthoridLam, EY=7102890004en_HK
dc.identifier.scopusauthoridWong, KKY=36456599700en_HK

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