Detection of Linear and Cubic Interpolation in JPEG Compressed Images
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Automatic Aerial Image RegistrationWithout Correspondence
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Robust Detection of Region-Duplication Forgery in Digital Image
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue
Proceedings of the 10th ACM workshop on Multimedia and security
Detection of Resampling Supplemented with Noise Inconsistencies Analysis for Image Forensics
ICCSA '08 Proceedings of the 2008 International Conference on Computational Sciences and Its Applications
Tampering identification using Empirical Frequency Response
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Exposing digital forgeries from JPEG ghosts
IEEE Transactions on Information Forensics and Security
Exposing digital forgeries by detecting traces of resampling
IEEE Transactions on Signal Processing
Exposing digital forgeries in color filter array interpolated images
IEEE Transactions on Signal Processing - Part II
Exposing Digital Forgeries in Complex Lighting Environments
IEEE Transactions on Information Forensics and Security - Part 1
Blind Authentication Using Periodic Properties of Interpolation
IEEE Transactions on Information Forensics and Security
Digital Image Forensics via Intrinsic Fingerprints
IEEE Transactions on Information Forensics and Security
Hiding Traces of Resampling in Digital Images
IEEE Transactions on Information Forensics and Security
Object based similarity measure for breast medical image retrieval from data warehouse
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Estimation of linear transformation by analyzing the periodicity of interpolation
Pattern Recognition Letters
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Motivated by the image rescaling estimation method proposed by Gallagher (2nd Canadian Conf. Computer & Robot Vision, 2005: 65-72), we develop an image rotation angle estimator based on the relations between the rotation angle and the frequencies at which peaks due to interpolation occur in the spectrum of the image's edge map. We then use rescaling/rotation detection and parameter estimation to detect fake objects inserted into images. When a forged image contains areas from different sources, or from another part of the same image, rescaling and/or rotation are often involved. In these geometric operations, interpolation is a necessary step. By dividing the image into blocks, detecting traces of rescaling and rotation in each block, and estimating the parameters, we can effectively reveal the forged areas in an image that have been rescaled and/or rotated. If multiple geometrical operations are involved, different processing sequences, i.e., repeated zooming, repeated rotation, rotation-zooming, or zooming-rotation, may be determined from different behaviors of the peaks due to rescaling and rotation. This may also provide a useful clue to image authentication.