Blind Authentication Using Periodic Properties of Interpolation
In this paper, we analyze and analytically describe the specific statistical changes brought into the covariance structure of signal by the interpolation process. We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blin...
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| Veröffentlicht in: | IEEE transactions on information forensics and security 2008-09, Vol.3 (3), p.529-538 |
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| creator | Mahdian, B. Saic, S. |
| description | In this paper, we analyze and analytically describe the specific statistical changes brought into the covariance structure of signal by the interpolation process. We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blind, efficient, and automatic method capable of finding traces of resampling and interpolation. The proposed method can be very useful in many areas, especially in image security and authentication. For instance, when two or more images are spliced together, to create high quality and consistent image forgeries, almost always geometric transformations, such as scaling, rotation, or skewing are needed. These procedures are typically based on a resampling and interpolation step. By having a method capable of detecting the traces of resampling, we can significantly reduce the successful usage of such forgeries. Among other points, the presented method is also very useful in estimation of the geometric transformations factors. |
| doi_str_mv | 10.1109/TIFS.2004.924603 |
| format | Article |
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We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blind, efficient, and automatic method capable of finding traces of resampling and interpolation. The proposed method can be very useful in many areas, especially in image security and authentication. For instance, when two or more images are spliced together, to create high quality and consistent image forgeries, almost always geometric transformations, such as scaling, rotation, or skewing are needed. These procedures are typically based on a resampling and interpolation step. By having a method capable of detecting the traces of resampling, we can significantly reduce the successful usage of such forgeries. Among other points, the presented method is also very useful in estimation of the geometric transformations factors.</description><identifier>ISSN: 1556-6013</identifier><identifier>EISSN: 1556-6021</identifier><identifier>DOI: 10.1109/TIFS.2004.924603</identifier><identifier>CODEN: ITIFA6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Authentication ; Blinds ; Derivatives ; Digital forgery ; Digital images ; Forensics ; Forgery ; Geometric transformation ; image forensics ; Interpolation ; interpolation detection ; Mathematical analysis ; Periodic structures ; Resampling ; resampling detection ; Security ; Signal analysis ; Signal processing ; Statistics ; Studies ; tampering detection</subject><ispartof>IEEE transactions on information forensics and security, 2008-09, Vol.3 (3), p.529-538</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2008</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c430t-b150b8df4f0c4422b75edb1fb97dede90ba3b1ec9c70d8b1c88e00ad78bcb8a53</citedby><cites>FETCH-LOGICAL-c430t-b150b8df4f0c4422b75edb1fb97dede90ba3b1ec9c70d8b1c88e00ad78bcb8a53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4540058$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4540058$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mahdian, B.</creatorcontrib><creatorcontrib>Saic, S.</creatorcontrib><title>Blind Authentication Using Periodic Properties of Interpolation</title><title>IEEE transactions on information forensics and security</title><addtitle>TIFS</addtitle><description>In this paper, we analyze and analytically describe the specific statistical changes brought into the covariance structure of signal by the interpolation process. We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blind, efficient, and automatic method capable of finding traces of resampling and interpolation. The proposed method can be very useful in many areas, especially in image security and authentication. For instance, when two or more images are spliced together, to create high quality and consistent image forgeries, almost always geometric transformations, such as scaling, rotation, or skewing are needed. These procedures are typically based on a resampling and interpolation step. By having a method capable of detecting the traces of resampling, we can significantly reduce the successful usage of such forgeries. Among other points, the presented method is also very useful in estimation of the geometric transformations factors.</description><subject>Authentication</subject><subject>Blinds</subject><subject>Derivatives</subject><subject>Digital forgery</subject><subject>Digital images</subject><subject>Forensics</subject><subject>Forgery</subject><subject>Geometric transformation</subject><subject>image forensics</subject><subject>Interpolation</subject><subject>interpolation detection</subject><subject>Mathematical analysis</subject><subject>Periodic structures</subject><subject>Resampling</subject><subject>resampling detection</subject><subject>Security</subject><subject>Signal analysis</subject><subject>Signal processing</subject><subject>Statistics</subject><subject>Studies</subject><subject>tampering detection</subject><issn>1556-6013</issn><issn>1556-6021</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpd0DFPwzAQBWALgUQp7EgsEQtTyjmxE2dCpaJQqRKVaGcrti_gKo2DnQz8e1KCGJjuhu-dTo-QawozSqG4366Wb7MEgM2KhGWQnpAJ5TyLM0jo6d9O03NyEcJ-cIxmYkIeHmvbmGjedx_YdFaXnXVNtAu2eY826K0zVkcb71r0ncUQuSpaNR361tU_9JKcVWUd8Op3Tslu-bRdvMTr1-fVYr6ONUuhixXloISpWAWasSRROUejaKWK3KDBAlSZKoq60DkYoagWAgFKkwullSh5OiV3493Wu88eQycPNmis67JB1wcpcg6i4AIGeftP7l3vm-E5KbIkS5OcFgOCEWnvQvBYydbbQ-m_JAV57FMe-5THPuXY5xC5GSMWEf844wyAi_QbPYxx4Q</recordid><startdate>20080901</startdate><enddate>20080901</enddate><creator>Mahdian, B.</creator><creator>Saic, S.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blind, efficient, and automatic method capable of finding traces of resampling and interpolation. The proposed method can be very useful in many areas, especially in image security and authentication. For instance, when two or more images are spliced together, to create high quality and consistent image forgeries, almost always geometric transformations, such as scaling, rotation, or skewing are needed. These procedures are typically based on a resampling and interpolation step. By having a method capable of detecting the traces of resampling, we can significantly reduce the successful usage of such forgeries. 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| ispartof | IEEE transactions on information forensics and security, 2008-09, Vol.3 (3), p.529-538 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Authentication Blinds Derivatives Digital forgery Digital images Forensics Forgery Geometric transformation image forensics Interpolation interpolation detection Mathematical analysis Periodic structures Resampling resampling detection Security Signal analysis Signal processing Statistics Studies tampering detection |
| title | Blind Authentication Using Periodic Properties of Interpolation |
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