Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010 · 268 citations · 15 references
Image ContentMachine VisionImage AnalysisEngineeringEdge DetectionPattern RecognitionMedian FilteringLinearity AssumptionInformation ForensicsImage ManipulationImage DenoisingSpatial FilteringImage ForensicsVideo ForensicsComputer VisionImage Enhancement
In digital image forensics, it is generally accepted that intentional manipulations of the image content are most critical and hence numerous forensic methods focus on the detection of such 'malicious' post-processing. However, it is also beneficial to know as much as possible about the general processing history of an image, including content-preserving operations, since they can affect the reliability of forensic methods in various ways. In this paper, we present a simple yet effective technique to detect median filtering in digital images-a widely used denoising and smoothing operator. As a great variety of forensic methods relies on some kind of a linearity assumption, a detection of non-linear median filtering is of particular interest. The effectiveness of our method is backed with experimental evidence on a large image database.
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Pattern Recognition and Machine Learning
Journal of Electronic Imaging · 2007 · 22K citations
Hany Farid · IEEE Signal Processing Magazine · 2009 · 892 citations
Steganalysis by subtractive pixel adjacency matrix
Tomáš Pevný, Patrick Bas, Jessica Fridrich · 2009 · 766 citations