LWT-DCT based Image Watermarking Scheme using Normalized SVD

Author(s): Rahul Dixit, Amita Nandal*, Arvind Dhaka, Vardan Agarwal, Yohan Varghese Kuriakose

Journal Name: Recent Advances in Computer Science and Communications
Formerly Recent Patents on Computer Science

Volume 14 , Issue 9 , 2021

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Background: Nowadays, information security is one of the most significant issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia.

Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media.

Method: The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image, which is then normalized, followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor.

Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation.

Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

Keywords: Discrete Cosine Transform (DCT); Image Authentication; Image Watermarking; Lifting Wavelet Transform (LWT); and Singular Value Decomposition (SVD).

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Article Details

Year: 2021
Published on: 21 August, 2020
Page: [2994 - 3009]
Pages: 16
DOI: 10.2174/2666255813999200821161656
Price: $95

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PDF: 189