Performance Analysis of Fractional Redundant Wavelet Transform for Watermarking Scheme
Harpal Singh1, Ramneek Kaur Brar2, Priyanka Kaushal3
1Dr. Harpal Singh, Professor, Department of Electronics and Communication Engineering Chandigarh Engineering College, Landran (Mohali), India.
2Ms. Ramneek Kaur Brar, M. Tech Research Scholar, Department of Electronics and Communication Engineering Chandigarh Engineering College, Landran (Mohali), India.
3Ms. Priyanka Kaushal, Associate Professor, Chandigarh Engineering College, Landran (Mohali), India.
Manuscript received on 09 August 2019 | Revised Manuscript received on 17 August 2019 | Manuscript Published on 26 August 2019 | PP: 47-52 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10080789S19/19©BEIESP DOI: 10.35940/ijitee.I1008.0789S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, an algorithm for digital image watermarking which utilizes the hybridization technique is presented. The hybrid technique is formulated by combining the Redundant Wavelet Transform (RDWT) with Fractional Fourier Transform (FrFT) and Singular Value Decomposition (SVD). In this technique, watermark information is embedded in the low frequency band of Redundant Wavelet Transform. To increase the robustness, FrFT is implemented on low frequency coefficients of RDWT. Experimental results have been demonstrated on the basis of Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), and Gradient Magnitude Similarity Deviation (GMSD). A comparable improvement is witnessed from the results in terms of qualitative and quantitative analysis. The experimental results prove to be robust against various image processing and geometrical attacks applied on the standard test images.
Keywords: Logo Watermarking, Fractional Fourier Transform (FrFT), Redundant Wavelet Transform (RDWT), Singular Value Decomposition (SVD), Gradient Magnitude Similarity Deviation (GMSD).
Scope of the Article: Measurement & Performance Analysis