Total views : 292
Semi-fragile Image Authentication based on CFD and 3-bit Quantization
There is a great adventure of watermarking usage in the context of conventional authentication since it does not require additional storage space for supplementary metadata. However, JPEG compression, being a conventional method to compress images, leads to exact authentication breaking. We discuss a semi-fragile watermarking system for digital images tolerant to JPEG/JPEG2000 compression. Recently we have published a selective authentication method based on Zernike moments. But unfortunately it has large computational complexity and not sufficiently good detection of small image modifications. In the current paper it is proposed (in contrast to Zernike moments approach) the usage of image finite differences and 3-bit quantization as the main technique. In order to embed watermark (WM) into the image, some areas of the Haar wavelet transform coefficients are used. Simulation results show a good resistance of this method to JPEG compression with CR≤30% (Compression Ratio), high probability of small image modification recognition, image quality assessments PSNR≥40 dB (Peak signal-to-noise ratio) and SSIM≥0.98 (Structural Similarity Index Measure) after embedding and lower computation complexity of WM embedding and extraction. All these properties qualify this approach as effective.
3-bit Hash Quantization, Central-finite Differences, Digital Images, Haar-wavelet Transform, JPEG2000, JPEG, Semi-fragile Authentication.
- Menezes AAJ, Van Oorschot P, Vanstone S. Handbook of applied crytography, ser. Discrete Mathematics and Its Applications Series. CRC Press; 1997.
- Lee MH, Korzhik VI, Morales-Luna G, Lusse S, Kurbatov E. Image authentication based on modular embedding. IEICE Transactions. 2006; 89-D(4):1498–1506.
- Goljan M, Fridrich JJ, Du R. Distortion-free data embedding for images. Proceedings of the 4th International Workshop on Information Hiding, ser. IHW ’01. London, UK, UK: Springer-Verlag; 2001. p. 27–41.
- Fridrich J, Goljan M, Du R. Invertible authentication watermark for JPEG images. ITCC. IEEE Computer Society; 2001. p. 223–7.
- Ni Z, Shi Y, Ansari N, Su W. Reversible data hiding. IEEE Transactions on Circuits and Systems for Video Technology. 2006; 16(3):354–62.
- Barni M, Bartolini F. Watermarking systems engineering: Enabling digital assets security and other applications, ser. Signal Processing and Communications. Marcel Dekker; 2004.
- Liu H, Yao X, Huang J. Semi-fragile Zernike moment-based image watermarking for authentication. EURASIP Journal on Advances in Signal Processing. 2010; 2010:10.
- Haouzia A, Noumeir R. Methods for image authentication: A survey. Multimedia Tools and Applications. 2008; 39(1):1–46.
- Han S-H, Chu C-H. Content-based image authentication: current status, issues, and challenges. International Journal of Information Security. 2009; 9(1):19–32.
- Dittmann J, Steinmetz A, Steinmetz R. Content-based digital signature for motion pictures authentication and content-fragile watermarking. IEEE International Conference on Multimedia Computing and Systems. 1999; 2:209–13.
- Gokhale U, Joshi Y. A semi fragile watermarking algorithm based on SVD-IWT for image authentication. International Journal of Advanced Research in Computer and Communication Engineering. 2012; 1(4).
- Mushtaq S, Mir AH. Digital image forgeries and passive image authentication techniques: A survey. International Journal of Advanced Science and Technology. 2014; 73:15– 32.
- Korzhik V, Zhuvikin A, Morales-Luna G. Selective image authentication tolerant to JPEG compression. 6th International Conference on Information, Intelligence, Systems and Applications (IISA 2015), ser. Ionian University, Corfu, Greece. IEEE Computer Society; 2015. p. 06–08.
- Eberly D. Derivative approximation by finite differences [Internet]. 2008. Available from: http://www.geometrictools.com.
- Dodgson NA. Image resampling, University of Cambridge, Computer Laboratory, Technical Report, UCAMCLTR-261; 1992.
- Ahmed F, Siyal MY. A robust and secure signature scheme for video authentication. 2007 IEEE, International Conference on Multimedia and Expo; 2007.
- Porwik P, Lisowska A. The Haar wavelet transform in digital image processing: Its status and achievements.International Journal of Machine Graphics & Vision. 2004; 13(1):79–98.
- Gallager RG. Low-density parity-check codes; 1963.
- Guruswami V. Iterative decoding of low-density parity check codes (a survey) [Internet]. 2006. Available from: https://arxiv.org/abs/cs/0610022.
- Mohammadi P, Ebrahimi-Moghadam A, Shirani S. Subjective and objective quality assessment of image: A survey [Internet]. 2014. Available from: https://arxiv.org/ abs/1406.7799.
- Huynh-Thu Q, Ghanbari M. Scope of validity of PSNR in image/video quality assessment. Electronics Letters. 2008; 44(1):800–1.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.