Encryption Image via Mutual Singular Value Decomposition
Commenced in January 2007
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Paper Count: 33093
Encryption Image via Mutual Singular Value Decomposition

Authors: Adil Al-Rammahi

Abstract:

Image or document encryption is needed through egovernment data base. Really in this paper we introduce two matrices images, one is the public, and the second is the secret (original). The analyses of each matrix is achieved using the transformation of singular values decomposition. So each matrix is transformed or analyzed to three matrices say row orthogonal basis, column orthogonal basis, and spectral diagonal basis. Product of the two row basis is calculated. Similarly the product of the two column basis is achieved. Finally we transform or save the files of public, row product and column product. In decryption stage, the original image is deduced by mutual method of the three public files.

Keywords: Image cryptography, Singular values decomposition.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099240

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[1] N. EL Abbadi, A. AL-Rammahi, M. EL-Kufi “Image Encryption Based On Singular Values Decomposition”, Science Publications, Journal Of Computer Science 10(7), 2014, Pp.1222-1230.
[2] G. Bhatnagar, Q. Wu, B. Raman“A Novel Image Encryption Framework Based on Markov Map and Singular Value Decomposition”, Springer, Image analysis and recognition, Lecture Notes in Computer Science, Volume 6754, 2011, pp 286-296.
[3] A. Abd El-Latif ; L. Li ; N. Wang ; Q. Li ; X. Niu “A New Image Encryption Based On Chaotic Systems And Singular Values Decomposition”, ProceedingsSPIE, Fourth International Conference on Digital Image Processing May 1, 2012.
[4] A. Tafti&R. Maarefdoust “Digital Images Encryption in Spatial Domain Based on Singular Value Decomposition and Cellular Automata”, International Journal of Computer Science and Information Security,Vol. 11, No. 4, April, 2013, pp. 121-125.
[5] M. Wang, W. Chen, “Digital image copyright protection scheme based on visual cryptography and singular value decomposition”, Optical Engineering Volume 46, Issue 6, May 2007,pp. 1-8.
[6] T. Rakotondraina& H. Razafindradina, “Authentication System Securing Index of Image using SVD and ECC”, International Journal of Computer Science and Network, Vol 2, Issue 1, 2013, pp. 76-78.
[7] B. Devi, K. Singh, S. Roy, “Dual Image Watermarking Scheme based on Singular Value Decomposition and Visual Cryptography in Discrete Wavelet Transform”, International Journal of Computer Applications, 5(6), July 2012, PP.
[8] P. Singh & S. Agarwal, “A Visual Cryptography Based Watermarking Scheme Incorporating the Concepts of Homogeneity Analysis and Singular Value Decomposition”, International Journal of Computer Applications Volume 80 , No 16, October 2013pp. 1-9.
[9] Y. Chanu, K Singh and T. Tuithung “Steganography Technique based on SVD”, International Journal of Research in Engineering and TechnologyVol. 1, No. 6, 2012 .pp.293-297.
[10] N. EL Abbadi, A. AL-Rammahi, M. ELnowany “Blind Fake Image Detection”, International Journal of Computer Science Issues, Vol. 10, Issue 4,No 1, July 2013, Pp.180-186.
[11] N. EL Abbadi, A. AL-Rammahi, M. EL-Kufi and D. Redha,“Image Compression Based on SVD AND MPQ-BTC”, Science Publications, Journal of Computer Science 10 (10), 2104, pp.2095-2104.
[12] B. Kolman, “Introductory linear algebra with applications ”, Macmillanpublishing company, New Work, 11e, 2009 .
[13] G. H. Golub and C. F. van Loan, “Matrix Computations”, 3rd ed, The Johns Hopkins University Press, Baltimore, 1996.
[14] A. Bovik, “The Essential Guide To Image Processing ”,Academicpress publication, 2009.