Local linear transforms for texture measurements
Signal Processing
Attack modelling: towards a second generation watermarking benchmark
Signal Processing - Special section on information theoretic aspects of digital watermarking
A Stochastic Approach to Content Adaptive Digital Image Watermarking
IH '99 Proceedings of the Third International Workshop on Information Hiding
Second Generation Benchmarking and Application Oriented Evaluation
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Bit-Plane Decomposition Steganography Combined with JPEG2000 Compression
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
A steganographic method for images by pixel-value differencing
Pattern Recognition Letters
Defending against statistical steganalysis
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
Detecting LSB matching by applying calibration technique for difference image
Proceedings of the 10th ACM workshop on Multimedia and security
Multi bit plane image steganography
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Adaptive Data Hiding in Edge Areas of Images With Spatial LSB Domain Systems
IEEE Transactions on Information Forensics and Security
Optimized Feature Extraction for Learning-Based Image Steganalysis
IEEE Transactions on Information Forensics and Security
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Pixel-value differencing (PVD) based steganography is one of popular approaches for secret data hiding in the spatial domain. However, based on extensive experiments, we find that some statistical artifacts will be inevitably introduced even with a low embedding capacity in most existing PVD-based algorithms. In this paper, we first analyze the common limitations of the original PVD and its modified versions, and then propose a more secure steganography based on a content adaptive scheme. In our method, a cover image is first partitioned into small squares. Each square is then rotated by a random degree of 0, 90, 180 or 270. The resulting image is then divided into non-overlapping embedding units with three consecutive pixels, and the middle one is used for data embedding. The number of embedded bits is dependent on the differences among the three pixels. To preserve the local statistical features, the sort order of the three pixel values will remain the same after data hiding. Furthermore, the new method can first use sharper edge regions for data hiding adaptively, while preserving other smoother regions by adjusting a parameter. The experimental results evaluated on a large image database show that our method achieves much better security compared with the previous PVD-based methods.