Detecting digital image forgeries using sensor pattern noise

By Jan Lukás, Jessica J. Fridrich, Miroslav Goljan. Electronic imaging, 2006

371 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/8798fac40256d375eaa730cc60cb82fe2124ebf4

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In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

Exposing Digital Forgeries in Complex Lighting Environments (2007, methodology): “Statistical techniques have been developed for detecting cloning [1], [2]; splicing [3]; resampling artifacts [4], [5]; color filter array aberrations [4]; and disturbances of a camera’s sensor noise pattern [6].”
Determining Image Origin and Integrity Using Sensor Noise (2008, background): “The second forensic task investigated in this paper is integrity verification, commonly known as forgery detection.”
Information Forensics: An Overview of the First Decade (2013, methodology): “If the PRNU of the camera that captured a digital image is known, it can be used to identify falsified regions in the image [102].”
Media Forensics and DeepFakes: An Overview (2020, methodology): “PRNU-based forgery detection was first proposed in [108] based on two steps: i) the camera PRNU pattern is estimated off-line from a large number of images taken from the camera,”
Digital image forensics via intrinsic fingerprints (2008, background): “Further, the estimates are shown to be robust to moderate levels of postprocessing operations, such as JPEG compression, and white balancing done inside the cameras [33].”
Noiseprint: A CNN-Based Camera Model Fingerprint (2018, methodology): “[28] it was observed that each individual device leaves a specific mark on all acquired”
Digital image forensics: a booklet for beginners (2010, methodology): “[64] propose to detect and localize tampering by analyzing the Multimed Tools Appl (2011) 51:133–162 149”
Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis (2009, background): “[16] require either the camera that took the images or other images taken by the same camera.”