COMPARATIVE ANALYSIS OF APPLICATION EFFICIENCY OF ORTHOGONAL TRANSFORMATIONS IN FREQUENCY ALGORITHMS FOR DIGITAL IMAGE WATERMARKING

V. A. Batura, A. J. Tropchenko


Read the full article  ';
Article in Russian


Abstract
The efficiency of orthogonal transformations application in the frequency algorithms of the digital watermarking of still images is examined. Discrete Hadamard transform, discrete cosine transform and discrete Haar transform are selected. Their effectiveness is determined by the invisibility of embedded in digital image watermark and its resistance to the most common image processing operations: JPEG-compression, noising, changing of the brightness and image size, histogram equalization. The algorithm for digital watermarking and its embedding parameters remain unchanged at these orthogonal transformations. Imperceptibility of embedding is defined by the peak signal to noise ratio, watermark stability– by Pearson's correlation coefficient. Embedding is considered to be invisible, if the value of the peak signal to noise ratio is not less than 43 dB. Embedded watermark is considered to be resistant to a specific attack, if the Pearson’s correlation coefficient is not less than 0.5. Elham algorithm based on the image entropy is chosen for computing experiment. Computing experiment is carried out according to the following algorithm: embedding of a digital watermark in low-frequency area of the image (container) by Elham algorithm, exposure to a harmful influence on the protected image (cover image), extraction of a digital watermark. These actions are followed by quality assessment of cover image and watermark on the basis of which efficiency of orthogonal transformation is defined. As a result of computing experiment it was determined that the choice of the specified orthogonal transformations at identical algorithm and parameters of embedding doesn't influence the degree of imperceptibility for a watermark. Efficiency of discrete Hadamard transform and discrete cosine transformation in relation to the attacks chosen for experiment was established based on the correlation indicators. Application of discrete Hadamard transform increases stability of embedded watermark to the brightness changing and histogram equalization of the cover image. Haar transform application showed the lowest efficiency. These results will be useful in creation of frequency algorithm for embedding a digital watermark into an image.

Keywords: Hadamard transformation, JPEG compression, steganography, digital watermarking, digital watermark

References
 1.     Gribunin V.G., Okov I.N., Turintsev V.I. Tsifrovaya Steganografiya [Digital Steganography]. Moscow, SOLON-Press Publ., 2002, 272 p.
2.     Su Q., Niu Y., Zhao Y., Pang S., Liu X. A dual color images watermarking scheme based on the optimized compensation of singular value decomposition. AEU – International Journal of Electronics and Communications, 2013, vol. 67, no. 8, pp. 652–664. doi: 10.1016/j.aeue.2013.01.009
3.     WuX., Sun W. Robust copyright protection scheme for digital images using overlapping DCT and SVD.Applied Soft Computing Journal, 2013,vol. 67, no. 2, pp. 1170–1182. doi: 10.1016/j.asoc.2012.09.028
4.     Patra J.C., Phua J.E., Bornand C. A novel DCT domain CRT-based watermarking scheme for image authentication surviving JPEG compression. Digital Signal Processing: A Review Journal, 2010,vol. 20, no. 6, pp. 1597–1611. doi: 10.1016/j.dsp.2010.03.010
5.     Bhatnagar G., Jonathan Wu Q.M. A new logo watermarking based on redundant fractional wavelet transform. Mathematical and Computer Modelling, 2013,vol. 58, no. 1–2, pp. 204–218. doi: 10.1016/j.mcm.2012.06.002
6.     Bhatnagar G., Jonathan Wu Q.M., Raman B. A new robust adjustable logo watermarking scheme. Computers and Security, 2012,vol. 31, no. 1, pp. 40–58. doi: 10.1016/j.cose.2011.11.003
7.     Maheswari S., Rameshwaran K. A robust blind image watermarking based on double Haar wavelet transform (DHWT). Journal of Scientific and Industrial Research, 2012,vol. 71, pp. 324–329.
8.     Maity S.P., Kundu M.K. DHT domain digital watermarking with low loss in image informations. AEU – International Journal of Electronics and Communications, 2010, vol. 64, no. 3, pp. 243–257. doi: 10.1016/j.aeue.2008.10.004
9.     Ho A.T.S., Shen J., Chow A.K.K., Woon J. Robust digital image-in-image watermarking algorithm using fast Hadamard transform. Proc. IEEE International Symposium on Circuits and Systems, 2003, vol. 3, pp. III826–III829.
10.Maity S.P., Kundu M.K. Perceptually adaptive spread transform image watermarking scheme using Hadamard transform. Information Sciences, 2011, vol. 181, no. 3, pp. 450–465. doi: 10.1016/j.ins.2010.09.029
11.Shabanali Fami E., Samavi S., Rezaee Kaviani H., Molaei Radani Z. Adaptive watermarking in Hadamard transform coefficients of textured image blocks. Proc. 16th International Symposium on Artificial Intelligence and Signal Processing. Shiraz, Iran, 2012, vol. 2012, art. 6313799, pp. 503–507. doi: 10.1109/AISP.2012.6313799
12.Saryazdi S., Nezamabadi-pour H. A blind digital watermark in Hadamard domain. International Journal of Computer, Information, Systems and Control Engineering, 2007, vol. 1, no. 3, pp. 784–787.
13.Razinkov E.V., Latypov R.Kh. Vstraivanie tsifrovogo vodyanogo znaka v izobrazhenie s ispol'zovaniem kompleksnogo preobrazovaniya Adamara [Embedding digital watermark into an image using a complex Hadamard transform]. Materialy II Mezhdunarodnoi Nauchnoi Konferentsii po Problemam Bezopasnosti i Protivodeistviya Terrorizmu [Proc. II Int. Scientific Conference on Security and Counter Terrorism]. Moscow, MTsNMO Publ., 2007, pp. 509–514.
14.Bhatnagar G., Raman B. Robust watermarking in multiresolution Walsh-Hadamard transform. 2009 IEEE International Advance Computing Conference, IACC 2009. Patiala, Infia, 2009, art. 4809134, pp. 894–899. doi: 10.1109/IADCC.2009.4809134
15.Sarker I.H., Iqbal S. Content-based image retrieval using Haar wavelet transform and color moment. Smart Computing Review, 2013, vol. 3, no. 3, pp. 155–165.
16.Ho A.T.S., Shen J., Tan S.H. A character-embedded watermarking algorithm using the fast Hadamard transform for satellite images. Proceedings of SPIE – The International Society for Optical Engineering, 2002, vol. 4793, pp. 156–167. doi: 10.1117/12.451249
17.Balonin Yu.N., Sergeev M.B. Algoritm i programma poiska i issledovaniya M-matrits [The algorithm and program of M-matrices search and study]. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2013, no. 3 (85), pp. 82–86.
18.Vostrikov A.A., Chernyshev S.A. Ob otsenke ustoichivosti k iskazheniyam izobrazhenii, maskirovannykh M-matritsami [On distortion assessment of images masking with M-matrices]. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2013, no. 5 (87), pp. 99–103.
19.Sayood K. Introduction to Data Compression. Morgan Kaufmann Publ., 1996, 491 p.


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright 2001-2024 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.

Яндекс.Метрика