TY - GEN
T1 - JPEG grid detection based on the number of DCT zeros and its application to automatic and localized forgery detection
AU - Nikoukhah, T.
AU - Anger, J.
AU - Ehret, T.
AU - Colom, M.
AU - Morel, J. M.
AU - Grompone von Gioi, R.
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2019/6/1
Y1 - 2019/6/1
N2 - This work proposes a novel method for detecting JPEG compression, as well as its grid origin, based on counting the number of zeros in the DCT of 8 × 8 blocks. When applied locally, the same method can be used to detect grid alignment abnormalities. It therefore detects local image forgeries such as copy-move. The algorithm includes a statistical validation step which gives theoretical guarantees on the number of false alarms and provides secure guarantees for tampering detection. The performance of the proposed method is illustrated with both quantitative and visual results from well-known image databases and comparisons with state of the art methods. © 2019 IEEE Computer Society. All rights reserved.
AB - This work proposes a novel method for detecting JPEG compression, as well as its grid origin, based on counting the number of zeros in the DCT of 8 × 8 blocks. When applied locally, the same method can be used to detect grid alignment abnormalities. It therefore detects local image forgeries such as copy-move. The algorithm includes a statistical validation step which gives theoretical guarantees on the number of false alarms and provides secure guarantees for tampering detection. The performance of the proposed method is illustrated with both quantitative and visual results from well-known image databases and comparisons with state of the art methods. © 2019 IEEE Computer Society. All rights reserved.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85090176004&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781728125060
VL - 2019-June
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 110
EP - 118
BT - Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
PB - IEEE Computer Society
T2 - 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Y2 - 16 June 2019 through 20 June 2019
ER -