IJCNIS Vol. 8, No. 4, 8 Apr. 2016
Cover page and Table of Contents: PDF (size: 717KB)
Full Text (PDF, 717KB), PP.14-21
Views: 0 Downloads: 0
Digital image steganography, copyright protection, singular value decomposition, Arnold transform, integer wavelet transform
This paper presents a new technique for copyright protection of images using integer wavelet transform (IWT), singular value decomposition (SVD) and Arnold transform. We divide the cover image into four sub-images by picking alternate pixels from consecutive rows and columns and embed the copyright mark into the sub-image having the largest sum of singular values. The embedding is done by modifying singular values of the IWT coefficients of the selected sub-image. The use of Arnold transform and SVD increases security and robustness against geometric and several signals processing attacks, while IWT provides computational efficiency. We compare the performance of our technique with state-of-the-art-methods. The experimental results show that the proposed technique is more imperceptible and achieves higher security and robustness against various signal processing (filtering, compression, noise addition, histogram equalization and motion blur) and geometrical (cropping, resizing, rotation) attacks.
Siddharth Singh, Tanveer J. Siddiqui, "Copyright Protection for Digital Images using Singular Value Decomposition and Integer Wavelet Transform", International Journal of Computer Network and Information Security(IJCNIS), Vol.8, No.4, pp.14-21, 2016. DOI:10.5815/ijcnis.2016.04.02
[1]N. F. Johnson and S. Jajodia, “Exploring Steganography: Seeing the unseen,” IEEE Computer, 1998, 31(2), pp. 26–34.
[2]Fridrich J., Steganography in Digital Media Principles, Algorithms and Application, Cambridge University Press, New York, 2010.
[3]Cheddad, J. Condell, K. Curran and Mc P. Kevitt, “Digital image Steganography: Survey and analysis of current methods,” Review Article, Signal Process., 2010; 90:727–752.
[4]C. Chang and J. C. Chung, “An image intellectual property protection scheme for gray-level images using visual secret sharing strategy,” Pattern Recognit. Letters, 2002; 23:pp. 931–941.
[5]S. L Hsieh. And B. Y. Huang, “A copyright protection scheme for gray-level images based on image secret sharing and wavelet transformation,” Proceedings of International Computer Symposium, 2004, pp. 661–666.
[6]C. S. Hsu and Y. C. Hou, “Copyright protection scheme for digital images using visual cryptography and sampling methods,” Optical Engg., 2005.
[7]Wang S.H., Lin Y.P., Wavelet tree quantization for copyright protection watermarking, IEEE Trans. Image Processing, 2004; 13(2): 154–165.
[8]R. Liu and T. Tan, “An SVD-based watermarking scheme for protecting rightful ownership,” IEEE Trans. Multimedia, 2002; 4(1), pp.121–128.
[9]G. Bhatnagar, Q. J. Wu and B. Raman, “A new aspect in robust digital watermarking,” Multimedia tools and applications, 2013, vol. 66(2), pp.179-200.
[10]G. Bhatnagar and B. Raman, “A new robust reference watermarking scheme based on DWT-SVD,” Comput. Stand. Interfaces, 2009, vol. 31, pp. 1002-1013.
[11]M. S.Wang and W. C. Chen, “A hybrid DWT-SVD copyright scheme based on K-mean clustering and visual cryptography,” Comput. Stand. Interfaces, 2009, vol. 31, pp. 750-762.
[12]S. Rawat and B. Raman, “Best tree wavelet packet transform based copyright protection scheme for digital image,” Optics Communi., 2012, vol. 285, pp. 2563-2574.
[13]E. Ganic, A. M. Eskicioglu, “Robust embedding of visual watermarks using DWT-SVD,” J. Electronic Imaging, 2005, vol. 14(4), pp. 043004-13.
[14]R Calderbank, I. Daubechies, W. Sweldens and B. L. Yeo, “Wavelet transforms that map integers to integers,” Appl. Computation Harmonic Analysis, 1998, 5(3), pp.332-369.
[15]W. Sweldens, “The lifting scheme: a construction of second generation wavelets,” SIAM J. Mathematical Analysis. 1998, vol. 29, pp.511–546.
[16]M. D. Adams and F. Kossentini, Reversible integer-to-integer wavelet transforms for image compression: performance evaluation and analysis, IEEE Trans. Image Process., 2000; vol. 9, 1010–1024.
[17]A. Phadikar and S. P. Maity, Data hiding based quality access control of digitals using adaptive QIM and lifting, Signal Process.: Image Communi., 2011; vol. 26, pp. 646-661.
[18]V. I. Arnold and A. Avez, “Ergodic problems in classical mechanics, Benjamin,” New York, 1968.
[19]R. Ye, “A novel chaos-based image encryption scheme with an efficient permutation-diffusion mechanism,” Optics Communicat., 2011, 284: 5290-5298.
[20]R. Kakarala and P. O. Ogunbona, “Signal analysis using a multiresolution form of the singular value decomposition,” IEEE Trans. Image Processing, 2001, vol. 10, pp. 724-735.
[21]C. C. Chang, P. Tsai and C. C.Lin, “SVD-based digital image watermarking scheme,” Pattern Recognit. Letters, 2005, vol.26, pp. 1577–1586.
[22]B. Zho and J. Chen. “A Geometric Distortion Resilient image Watermarking Algorithm Based SVD,” Chinese J. Image Graphics, 2004, vol. 9, pp.506–512.
[23]M. Arsalan, S. A. Malik and A. Khan, Intelligent reversible watermarking in integer wavelet domain for medical images, J. of System and Software, 2012, vol. 85(4), pp. 883–894.
[24]S. Singh and T. J. Siddiqui, Robust Image Data Hiding Technique for Copyright Protection, International Journal of Information Security and Privacy, 2013, vol.7(2), pp. 44-56.