Secure hybrid robust watermarking resistant against tampering and copy attack
Signal Processing - Special section: Security of data hiding technologies
Fragile image watermarking using a gradient image for improved localization and security
Pattern Recognition Letters
A majority-voting based watermarking scheme for color image tamper detection and recovery
Computer Standards & Interfaces
Dual watermark for image tamper detection and recovery
Pattern Recognition
Improving Capability of Locating Tampered Pixels of Statistical Fragile Watermarking
IWDW '09 Proceedings of the 8th International Workshop on Digital Watermarking
A wavelet-based fragile watermarking scheme for secure image authentication
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Reversible Image Watermarking Based on Integer-to-Integer Wavelet Transform
IEEE Transactions on Information Forensics and Security - Part 1
Fragile Watermarking Based on Encoding of the Zeroes of the -Transform
IEEE Transactions on Information Forensics and Security
Counterfeiting attacks on oblivious block-wise independent invisible watermarking schemes
IEEE Transactions on Image Processing
Secret and public key image watermarking schemes for image authentication and ownership verification
IEEE Transactions on Image Processing
Hierarchical watermarking for secure image authentication with localization
IEEE Transactions on Image Processing
Multi-block dependency based fragile watermarking scheme for fingerprint images protection
Multimedia Tools and Applications
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Statistical fragile watermarking is capable of accurately locating tampered pixels and resisting the collage attack. However, the constraint of the tamper ratio may be too stringent. This paper proposes a neighborhood characteristic based detection model for statistical fragile watermarking to lift the constraints of the tampered area from 4% to 14% of the host image. The neighborhood characteristic is used to effectively decrease the probability of false rejection, while the low probability of false acceptance is guaranteed by selecting proper threshold. The tamper detection performance of the proposed detection model is analytical analyzed in the different conditions. Analytical and experimental results demonstrate that the neighborhood characteristic based detection model effectively reduce the total number of false decisions and detect the tampered pixels with high probability.