Abstract
The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of data. This article introduces a self-embedded image verification and integrity scheme. The images are firstly split into dedicated segments of the same block sizes. Then, different Analytic Beta-Wavelet (ABW) orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined method. ABW orthogonal filter coefficients are estimated to improve image reconstruction under different block sizes. We conduct a comparative study comparing the watermarked images using three kinds of ABW filters for block sizes 64 × 64, 128 × 128, and 256 × 256. We embed the watermark using the ABW-based image watermarking method in the 2-level middle frequency sub-bands of the ABW digital image coefficients. The imperceptibility and robustness of the ABW-based image watermarking method image is evaluated based on the Peak Signal to Noise Ratio (PSNR) and Correlation coefficient values. From the implementation results, we came to know that this ABW-based image watermarking method can withstand many image manipulations compared to other existing methods.
Highlights
Data security becomes an essential issue in the digital world with the rapid growth of digital images and Internet technology accompanied by many security threats on the Internet
The frequencydomain encryption algorithms use some common transforms like discrete cosine transform (DCT), discrete Fourier transform (DFT), and discrete wavelet transform (DWT) to transform the images from spatial to frequency domain first and get the frequency coefficients and change their positions through those specific rules [8]
5.2 Watermarking Using Beta Wavelets The watermark is embedded into images by applying the safeguard method to the beta wavelets approximation coefficients at level 2
Summary
For this purpose, many image encryption technologies have emerged and proposed. The frequencydomain encryption algorithms use some common transforms like discrete cosine transform (DCT), discrete Fourier transform (DFT), and discrete wavelet transform (DWT) to transform the images from spatial to frequency domain first and get the frequency coefficients and change their positions through those specific rules [8]. The rest of the paper is organized as follows: Section 2 presents the mathematical background of the parametric Beta Wavelets proposed in the schemas of protection and verification of the encrypted images.
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