A semi-fragile lossless digital watermarking based on adaptive threshold for image authentication

In this paper, a novel semi-fragile lossless digital watermarking method based on adaptive threshold for image authentication is presented. Most of the existing semi-fragile lossless watermarking schemes are based on modulo-256 addition to achieve losslessness. In order to avoid the salt-and-pepper noise, some of the schemes ignore the blocks which lead to overflow/underflow, and using error correction codes (ECCs). But the ECC will reduce available embedding capacity, especially for the complex images. We then propose an adaptive threshold method to improve the existing schemes. By employing a robust statistical quantity based on the patchwork to embed data, identifying image complexity based on wavelet-domain generalised Gaussian distribution (GGD) and using it to adaptively quantise thresholds which differentiating the embedding process, and using simple ECC, this technique has achieved losslessness, robustness and more competitive available embedding capacity. Experimental results demonstrate that the capacity of watermarked image of this technique is highly improved, and the quality of the image is acceptable.

[1]  Yang Fan A Semi-fragile Digital Watermark for Image Content Authentication , 2011 .

[2]  Yun Q. Shi,et al.  Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking , 2010, Int. J. Digit. Crime Forensics.

[3]  Eero P. Simoncelli,et al.  On Advances in Statistical Modeling of Natural Images , 2004, Journal of Mathematical Imaging and Vision.

[4]  Yun Q. Shi,et al.  A content-based image authentication system with lossless data hiding , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[5]  Yun Q. Shi,et al.  Lossless data hiding: fundamentals, algorithms and applications , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[6]  Yun Q. Shi,et al.  A semi-fragile lossless digital watermarking scheme based on integer wavelet transform , 2004, IEEE 6th Workshop on Multimedia Signal Processing, 2004..

[7]  Zhicheng Ni,et al.  Distortionless data hiding based on integer wavelet transform , 2002 .

[8]  Zhang Xiong,et al.  Visual data security and management for smart cities , 2010, Frontiers of Computer Science in China.

[9]  Martin J. Wainwright,et al.  Scale Mixtures of Gaussians and the Statistics of Natural Images , 1999, NIPS.

[10]  Qingzhong Liu,et al.  Image complexity and feature mining for steganalysis of least significant bit matching steganography , 2008, Inf. Sci..

[11]  Rui Du,et al.  Invertible authentication watermark for JPEG images , 2001, Proceedings International Conference on Information Technology: Coding and Computing.

[12]  Christophe De Vleeschouwer,et al.  Circular interpretation of bijective transformations in lossless watermarking for media asset management , 2003, IEEE Trans. Multim..

[13]  Wei Su,et al.  Reversible data hiding , 2006, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Shih-Fu Chang,et al.  New semi-fragile image authentication watermarking techniques using random bias and nonuniform quantization , 2006, IEEE Transactions on Multimedia.

[15]  David Mumford,et al.  Statistics of natural images and models , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[16]  Wei Su,et al.  Robust Lossless Image Data Hiding Designed for Semi-Fragile Image Authentication , 2008, IEEE Transactions on Circuits and Systems for Video Technology.