LWT–DSR based new robust framework for watermark extraction under intentional attack conditions. Issue 14 (September 2017)

• Record Type: Journal Article
• Authors: Verma, Vivek Singh; Jha, Rajib Kumar
• Is Part Of: Journal of the Franklin Institute. Volume 354:Issue 14(2017)
• Page Start: 6422
• Page End: 6449
• Publication Date: 2017-09
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2017.07.032
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: This paper proposes a new watermarking approach using dynamic stochastic resonance (DSR) based tuning operation to extract the watermark logo from the watermarked image that has undergone different intentional and signal processing attacks. This method is intended to provide remedies from the shortcomings of the technique proposed by Lin et al. (2008), and invalidates the effect of intentional attacks recently designed by Meerwald et al. (2009). The algorithm incorporates three level image decomposition using lifting wavelet transform (LWT) and low-pass subband is utilized for data hiding purpose. Watermark bits are embedded into the blocks of non-overlapped wavelet coefficients of the cover image by quantizing the two maximum coefficients of the corresponding block. In watermark extraction process, the DSR is applied by performing the tuning operation on coefficient blocks of attacked watermarked image. It is a parameter dependent approach that enhances the performance of watermark extraction, where the parameters of DSR inherently depend on the image properties such as standard deviation or variance. As far as security is concerned, the randomization of wavelet coefficients, blocks, and watermark bits helps the framework to be more secure. The proposed technique is also examined against multiple watermarking attack and successfully proves its authenticity and ownership. Comparison of the proposed technique with recent techniques shows remarkable improvement in terms of robustness and security against various intentional, signal processing, and geometrical attacks.