Abstract
This paper proposes a watermarking scheme, which combine both singular value decomposition (SVD) and discrete wavelet transform (DWT) based watermarking techniques. In addition to this, the paper introduces multi-level compression on the watermark image to improve the visual quality of the watermarked image. This can be achieved in two levels. In first level, compression is done by applying sampling and quantization on discrete cosine transform (DCT) coefficients. Then in the second level compression is carried out by principal component analysis (PCA). The proposed method is compared with various existing watermarking schemes by using image quality measures like peak signal to noise ratio (PSNR), mean structural similarity index (MSSIM) and correlation coefficient. It is observed that the proposed approach survives unintentional linear attacks such as rescaling, rotation and some minor modifications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Potdar, V.M., Han, S., Chang, E.: A Survey of Digital Image Watermarking Techniques. In: IEEE International Conference on Industrial Informatics (INDIN-03), pp. 709–716 (2005)
Huang, C.-H., Wu, J.-L.: Attacking Visible Watermarking Schemes. IEEE Transactions on Multimedia 1, 16–30 (2004)
Hsieh, M.-S., Tseng, D.-C.: Hiding digital watermarks using multi-resolution wavelet transform. IEEE Transactions on Industrial Electronics 48, 875–882 (2001)
Ruizhen, L., Tan, T.: An SVD based watermarking scheme for protecting rightful ownership. IEEE Transactions on Multimedia 4, 121–128 (2002)
Koteswara Rao, G., Srinivaskausalyanandan, T.P., Prashanth, R.L., Anuragh, V.: A Novel Approach In Image Watermarking With Discrete Wavelet Transform. In: The Proceedings of International Conference on Electrical and Electronics Engineering (ICEEE), pp. 120–123 (2012)
Shuo-Zhong, W.: Watermarking based on Principal component analysis. Journal of Shanghai University 4, 22–26 (2000)
Wan, Y.H., Yuan, Q.L., Ji, S.M., He, L.M., Wang, Y.L.: A survey of the image copy detection. In: IEEE Conference on Cybernetics and Intelligent Systems, pp. 738–743 (2008)
Benjamin, M., Cayre, F., Bas, P., Macq, B.: Optimal transport for secure spread-spectrum watermarking of still images, p. 1 (2014)
Swanirbhar, M., Devi, K.J., Sarkar, S.K.: Singular value decomposition and wavelet-based iris biometric watermarking. IET on Biometrics 2, 21–27 (2013)
Angela, P., Safavi-Naini, R.: Scalable fragile watermarking for image authentication. IET on Information Security 4, 300–311 (2013)
Ming, L., Kulhandjian, M.K., Pados, D.A., Batalama, S.N., Medley, M.J.: Extracting Spread-Spectrum Hidden Data from Digital Media. IEEE Transactions on Information Forensics and Security 8, 1201–1210 (2013)
http://www.petitcolas.net/fabien/watermarking/image_database/ (May 2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ayesha, S., Manikandan, V.M., Masilamani, V. (2015). A Combined SVD-DWT Watermarking Scheme with Multi-level Compression Using Sampling and Quantization on DCT Followed by PCA. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-11933-5_16
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11932-8
Online ISBN: 978-3-319-11933-5
eBook Packages: EngineeringEngineering (R0)