Robust image watermarking based on QR factorization and LWT
Abstract
Personal information needs to be safely transmitted over the internet and addressed effectively. Robust watermarking of biometric patterns is a convenient technique used to increase security and data authentication, which is decisive due to the uniqueness of some types of watermark images. Biometrics like fingerprints, voice, retina, iris, and blood vessel tree are being increasingly utilized for affirmative identification since they cannot be mislaid or forgotten and represent perceptible components. Furthermore, from the viewpoint of linear algebra, any digital image can be expressed by a matrix consists of a non-negative number of scalars. The objective of this paper is to intro-duce a newfangled blind watermarking algorithm using matrix decomposition method named QR. The application and analysis of the QR Matrix decomposition technique illustrate its impact on each block of the LH2 subband in the frequency domain that represents the output of two-level LWT (Lifting Wavelet Transform). The experimental results display that the newly proposed mechanism is secure and imperceptible. The final conclusion shows that the proposed method can get better PSNRs and that the proposed algorithm fulfills better watermark imperceptibility and robustness beneath different attacks.
About this article
Keywords
- Imperceptibility
- Lifting Wavelet Transform (LWT)
- QR Matrix Factorization
- Robustness
- Watermarking.
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