Using noise inconsistencies for blind image forensics
Image and Vision Computing
Intrinsic sensor noise features for forensic analysis on scanners and scanned images
IEEE Transactions on Information Forensics and Security
Statistical tools for digital forensics
IH'04 Proceedings of the 6th international conference on Information Hiding
Digital camera identification from sensor pattern noise
IEEE Transactions on Information Forensics and Security
Determining Image Origin and Integrity Using Sensor Noise
IEEE Transactions on Information Forensics and Security
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Noise is unwanted in high quality images, but it can aid image tampering. For example, noise can be intentionally added in image to conceal tampered regions and to create special visual effects. It may also be introduced unnoticed during camera imaging process, which makes the noise levels inconsistent in splicing images. In this paper, we propose a method to expose such image forgeries by detecting the noise variance differences between original and tampered parts of an image. The noise variance of local image blocks is estimated using a recently developed technique, where no prior information about the imaging device or original image is required. The tampered region is segmented from the original image by a two-phase coarse-to-fine clustering of image blocks. Our experimental results demonstrate that the proposed method can effectively detect image forgeries with high detection accuracy and low false positive rate both quantitatively and qualitatively.