Detection of Linear and Cubic Interpolation in JPEG Compressed Images
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue
Proceedings of the 10th ACM workshop on Multimedia and security
Parametric Estimation of Affine Transformations: An Exact Linear Solution
Journal of Mathematical Imaging and Vision
Linear row and column predictors for the analysis of resized images
Proceedings of the 12th ACM workshop on Multimedia and security
IEEE Transactions on Information Forensics and Security
"Break our steganographic system": the ins and outs of organizing BOSS
IH'11 Proceedings of the 13th international conference on Information hiding
An energy-based method for the forensic detection of Re-sampled images
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
Exposing digital forgeries by detecting traces of resampling
IEEE Transactions on Signal Processing
Blind Authentication Using Periodic Properties of Interpolation
IEEE Transactions on Information Forensics and Security
Digital Image Forensics: There is More to a Picture than Meets the Eye
Digital Image Forensics: There is More to a Picture than Meets the Eye
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Linear transformation, such as rotation, scaling, or any combinations of geometric attacks, is among the most common forms of image manipulation. This letter proposes a forensic technique that estimates the linear transformation of an investigated image. We exploited the periodic properties of interpolation by the second-derivative of the transformed image in both the row and column directions. Both the magnitude and phase information of the derived signals were analyzed to estimate the transformation matrix accurately. Empirical evidence from a large database of manipulated images indicates the superior performance of the proposed method.