Vector quantization and signal compression
Vector quantization and signal compression
Elements of information theory
Elements of information theory
Convex Optimization
Exposing digital forgeries in scientific images
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
Exposing digital forgeries through chromatic aberration
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
Rate-adaptive codes for distributed source coding
Signal Processing - Special section: Distributed source coding
Blind watermarking applied to image authentication
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Rate allocation for robust video streaming based on distributed video coding
Image Communication
Exposing digital forgeries through specular highlights on the eye
IH'07 Proceedings of the 9th international conference on Information hiding
Robust and secure image hashing
IEEE Transactions on Information Forensics and Security
Cocktail watermarking for digital image protection
IEEE Transactions on Multimedia
Signal Reconstruction From Noisy Random Projections
IEEE Transactions on Information Theory
Compressed Sensing and Redundant Dictionaries
IEEE Transactions on Information Theory
Hierarchical watermarking for secure image authentication with localization
IEEE Transactions on Image Processing
Compressive sensing-based image hashing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Image distortion estimation by hash comparison
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Dual Function Seal: Visualized Digital Signature for Electronic Medical Record Systems
Journal of Medical Systems
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In the last decade, the increased possibility to produce, edit, and disseminate multimedia contents has not been adequately balanced by similar advances in protecting these contents from unauthorized diffusion of forged copies. When the goal is to detect whether or not a digital content has been tampered with in order to alter its semantics, the use of multi-media hashes turns out to be an effective solution to offer proof of legitimacy and to possibly identify the introduced tampering. We propose an image hashing algorithm based on compressive sensing principles, which solves both the authentication and the tampering identification problems. The original content producer generates a hash using a small bit budget by quantizing a limited number of random projections of the authentic image. The content user receives the (possibly altered) image and uses the hash to estimate the mean square error distortion between the original and the received image. In addition, if the introduced tampering is sparse in some orthonormal basis or redundant dictionary, an approximation is given in the pixel domain. We emphasize that the hash is universal, e.g., the same hash signature can be used to detect and identify different types of tampering. At the cost of additional complexity at the decoder, the proposed algorithm is robust to moderate content-preserving transformations including cropping, scaling, and rotation. In addition, in order to keep the size of the hash small, hash encoding/decoding takes advantage of distributed source codes.