A new robust and secure digital image watermarking scheme based on the integer wavelet transform and singular value decomposition

2014 ◽  
Vol 33 ◽  
pp. 134-147 ◽  
Author(s):  
Nasrin M. Makbol ◽  
Bee Ee Khoo
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Digital Image ◽  
Image Watermarking ◽  
Singular Value ◽  
Digital Image Watermarking ◽  
Integer Wavelet Transform ◽  
Value Decomposition ◽  
Integer Wavelet ◽  
Watermarking Scheme

scholarly journals An Improvement in Digital Image Watermarking Scheme Based on Singular Value Decomposition and Wavelet Transform

2019 ◽  
Vol 8 (1) ◽  
pp. 62-68
Author(s):  
Manasha Saqib ◽  
Sameena Naaz
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Digital Image ◽  
Digital Signature ◽  
Image Watermarking ◽  
Singular Value ◽  
Digital Image Watermarking ◽  
Lifting Wavelet Transform ◽  
Value Decomposition ◽  
Watermarking Scheme

An enormous growth of multimedia information in the internet has given rise to varied unauthorized use and modification. This authenticity issue is equally a limitation both in the defense data transmission and secured transmission. Digital watermarking is one of the legitimate solutions to the above problem since it makes possible validation and secure transmission of secret data. This paper presents a robust and secure digital image watermarking scheme that can be used for copyright protection. The scheme involves Lifting Wavelet Transform (LWT) and Singular Value Decomposition (SVD). The latest approach to wavelet transform is the Lifting Wavelet Transform and the significant transform technique for robust digital image watermarking is Singular Value Decomposition. The results are cross-validated by using inverse LWT and SVD. The digital signature mechanism is used to generate and embed a digital signature after the watermark is embedded, then the ownership is authenticated before extracting watermarks. In order to check the robustness of the method against various common image processing attacks like Mean, Median, Gaussian, Shear, Rotation and Crop, certain performance metrics such as peak to signal noise ratio (PSNR)and mean square error (MSE) is computed. To check similarity, normal cross-correlation (NCC) is used.

scholarly journals Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels

2019 ◽  
Vol 9 (3) ◽  
pp. 2185 ◽  
Author(s):  
Ferda Ernawan ◽  
Dhani Ariatmanto
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Watermarking ◽  
Threshold Value ◽  
Singular Value ◽  
Multimedia Data ◽  
Optimal Threshold ◽  
Integer Wavelet Transform ◽  
Value Decomposition ◽  
Integer Wavelet

With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8×8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack.

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