Detecting Doctored Images Using Camera Response Normality and Consistency
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Source camera identification using enhanced sensor pattern noise
IEEE Transactions on Information Forensics and Security
Exposing digital forgeries by detecting traces of resampling
IEEE Transactions on Signal Processing
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Multimedia Forensics has become important in the last few years. There are two main interests, namely source identification and forgery detection. Source identification focuses on identifying the source digital devices (cameras, mobile phones, camcorders, etc) using the media produced by them, while forgery detection attempts to discover evidence of tampering by assessing the authenticity of the digital media (audio clips, video clips, images, etc). In this paper, we propose a novel source camera identification method based on detection and matching of dustspot characteristics that settle in front of the imaging sensor create a persistent pattern in all captured images of digital single lens reflex camera. To prevent false detections, lens parameter dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and down sampling.