Fundamentals of digital image processing
Fundamentals of digital image processing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Desktop Scanners: Image Quality Evaluation
Desktop Scanners: Image Quality Evaluation
Exposing digital forgeries in color filter array interpolated images
IEEE Transactions on Signal Processing - Part II
Steganalysis using higher-order image statistics
IEEE Transactions on Information Forensics and Security
Digital camera identification from sensor pattern noise
IEEE Transactions on Information Forensics and Security
Robust and secure image hashing
IEEE Transactions on Information Forensics and Security
Blind Identification of Source Cell-Phone Model
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
Approximate image message authentication codes
IEEE Transactions on Multimedia
A survey of forensic characterization methods for physical devices
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Spatially adaptive wavelet thresholding with context modeling for image denoising
IEEE Transactions on Image Processing
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
Steganalysis using image quality metrics
IEEE Transactions on Image Processing
Source camera identification using enhanced sensor pattern noise
IEEE Transactions on Information Forensics and Security
Region duplication detection using image feature matching
IEEE Transactions on Information Forensics and Security
Exposing image forgery with blind noise estimation
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security
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A large portion of digital images available today are acquired using digital cameras or scanners. While cameras provide digital reproduction of natural scenes, scanners are often used to capture hard-copy art in a more controlled environment. In this paper, new techniques for nonintrusive scanner forensics that utilize intrinsic sensor noise features are proposed to verify the source and integrity of digital scanned images. Scanning noise is analyzed from several aspects using only scanned image samples, including through image denoising, wavelet analysis, and neighborhood prediction, and then obtain statistical features from each characterization. Based on the proposed statistical features of scanning noise, a robust scanner identifier is constructed to determine the model/brand of the scanner used to capture a scanned image. Utilizing these noise features, we extend the scope of acquisition forensics to differentiating scanned images from camera-taken photographs and computer-generated graphics. The proposed noise features also enable tampering forensics to detect postprocessing operations on scanned images. Experimental results are presented to demonstrate the effectiveness of employing the proposed noise features for performing various forensic analysis on scanners and scanned images.