Digital Image Processing
Radiometric CCD camera calibration and noise estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exposing digital forgeries by detecting inconsistencies in lighting
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Physics-motivated features for distinguishing photographic images and computer graphics
Proceedings of the 13th annual ACM international conference on Multimedia
Exposing digital forgeries through chromatic aberration
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
Statistical tools for digital forensics
IH'04 Proceedings of the 6th international conference on Information Hiding
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
Determining Image Origin and Integrity Using Sensor Noise
IEEE Transactions on Information Forensics and Security
Digital Image Forensics via Intrinsic Fingerprints
IEEE Transactions on Information Forensics and Security
Nonintrusive Component Forensics of Visual Sensors Using Output Images
IEEE Transactions on Information Forensics and Security
Detection of Double-Compression in JPEG Images for Applications in Steganography
IEEE Transactions on Information Forensics and Security
Blind inverse gamma correction
IEEE Transactions on Image Processing
Digital image forensics: a booklet for beginners
Multimedia Tools and Applications
A universal technique to hide traces of histogram-based image manipulations
Proceedings of the on Multimedia and security
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As the use of digital images has increased, so has the means and the incentive to create digital image forgeries. Accordingly, there is a great need for digital image forensic techniques capable of detecting image alterations and forged images. A number of image processing operations, such as histogram equalization or gamma correction, are equivalent to pixel value mappings. In this paper, we show that pixel value mappings leave behind statistical traces, which we shall refer to as a mapping's intrinsic fingerprint, in an image's pixel value histogram. We then propose forensic methods for detecting general forms globally and locally applied contrast enhancement as well as a method for identifying the use of histogram equalization by searching for the identifying features of each operation's intrinsic fingerprint. Additionally, we propose a method to detect the global addition of noise to a previously JPEG-compressed image by observing that the intrinsic fingerprint of a specific mapping will be altered if it is applied to an image's pixel values after the addition of noise. Through a number of simulations, we test the efficacy of each proposed forensic technique. Our simulation results show that aside from exceptional cases, all of our detection methods are able to correctly detect the use of their designated image processing operation with a probability of 99% given a false alarm probability of 7% or less.