Parallel blind semi-fragil color image watermarking based on fast discrete cosine transform

Abstract. Comparison of Image Watermarking with the Wavelet Variety Packs and Discrete Cosine Transform. Watermarking is one method of copyright protection to combat the spread of the work of someone illegally. In this study, we compare watermarking algorithm in wavelet region and Discrete Cosine Transform (DCT). Color image is used as the host image, while the watermark image is used as a binary image of size 1 / 16 image of the host. Embedding process is based on Human Visual System (HVS), so hopefully gained an invisible watermark (invisible watermark). Embedding process performed by the additive algorithm. In both variety packs developed, the watermark is inserted in the high frequency components of the image. Wavelet used is the wavelet db4. DCT 4x4 blocks are used, which is expected to reduce the computational load. Tests showed that the two watermarking algorithms are generally resistant to granting noise, geometric image operations and image processing operations. Watermarking algorithm that was developed less defend against attacks-down pass filter and median filter, but has a very good performance against an attack-pass filter above. Keywords: image watermarking, wavelet, Discrete Cosine Transform (DCT), Human Visual System (HVS)Â Abstrak. Watermarking merupakan salah satu metode proteksi hak cipta untuk menanggulangi penyebaran karya seseorang secara ilegal. Pada penelitian ini dilakukan perbandingan algoritma watermarking pada kawasan wavelet dan Discrete Cosine Transform (DCT). Citra warna digunakan sebagai citra host, sedangkan sebagai citra watermark digunakan citra biner berukuran 1/16 citra host. Proses embedding dilakukan berdasarkan Human Visual System (HVS), sehingga diharapkan diperoleh watermark yang tidak kelihatan (invisible watermark). Proses embedding dilakukan dengan algoritma aditif. Pada kedua alihragam yang dikembangkan, watermark disisipkan pada komponen frekuensi tinggi citra. Wavelet yang digunakan adalah wavelet db4. Sedangkan alihragam DCT yang digunakan adalah operasi blok 4x4, yang diharapkan dapat mengurangi beban komputasi. Pengujian menunjukkan bahwa kedua algoritma watermarking secara umum tahan terhadap pemberian derau, operasi geometris citra dan operasi-operasi pengolahan citra. Algoritma watermarking yang dikembangkan kurang bertahan terhadap serangan-serangan tapis lolos-bawah dan tapis median, namun mempunyai unjuk kerja yang sangat baik terhadap serangan tapis lolos-atas.Â Kata Kunci: watermarking citra, wavelet, Discrete Cosine Transform (DCT), Human Visual System (HVS)

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LWT-DCT based Image Watermarking Scheme using Normalized SVD

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200821161656 ◽

2020 ◽

Vol 13 ◽

Author(s):

Rahul Dixit ◽

Amita Nandal ◽

Arvind Dhaka ◽

Vardan Agarwal ◽

Yohan Varghese

Keyword(s):

Wavelet Transform ◽

Singular Value Decomposition ◽

Discrete Cosine Transform ◽

Image Watermarking ◽

Singular Value ◽

Cover Image ◽

Lifting Wavelet Transform ◽

Cosine Transform ◽

Lifting Wavelet ◽

Value Decomposition

Background: Nowadays information security is one of the biggest 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.

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