Blind reliable invisible watermarking method in wavelet domain for face image watermark

Agarwal, Himanshu; Raman, Balasubramanian; Venkat, Ibrahim

doi:10.1007/s11042-014-1934-1

Cited by 25 publications

(7 citation statements)

References 62 publications

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“…Only electronic devices or specialized software can extract the hidden information to identify the copyright owner [5]. Invisible watermarks are used to mark a specialized digital content, for example text, images, audio to prove its authenticity [6].…”

Section: Digital Watermarkingmentioning

confidence: 99%

A Digital Image Watermarking System: An Application of Dual Layer Watermarking Technique

Phin

Rahman

2017

JOIV : Int. J. Inform. Visualization

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Abstract-Watermarking is a method to digitally sign a product to provide authentication and prevent copyright infringement to proving the ownership of a product and provides integrity for companies to protect their product. In this study, dual layer watermark that applies two different watermarking techniques at each layer is presented. The first layer applies the LSB Substitution technique while the second layer uses the Discrete Wavelet Transform (DWT) technique. This implies greater integrity as it contains of two signatures in providing authentication.

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Section: Digital Watermarkingmentioning

confidence: 99%

A Digital Image Watermarking System: An Application of Dual Layer Watermarking Technique

Phin

Rahman

2017

JOIV : Int. J. Inform. Visualization

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“…In the second set, biometric data is embedded into natural images to protect intellectual property rights and copyright. Various biometric data such as speech signal [10,11], fingerprint [12][13][14], face [15,16], iris [17][18][19][20], and signature [21] are used as watermark for this purpose. Authors in [18] and [19] embedded iris code into cover image using Discrete Wavelet Transform (DWT)-Singular Value Decomposition (SVD)-based and Discrete Cosine Transform (DCT)-SVD-based hybrid watermarking schemes, respectively.…”

Section: Introductionmentioning

confidence: 99%

Biometric Watermarking Schemes Based on QR Decomposition and Schur Decompositon in RIDWT Domain

Altay

Ulutaş

2023

Preprint

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In this paper, two new methods are proposed to hide a biometric-based digital watermark generated from an iris image into a color image to resolve ownership conflicts. One of them is the QR decomposition-based approach in the redistributed invariant discrete wavelet transform (RIDWT) domain, and the other is the Schur decomposition-based approach in the RIDWT domain. After the Y channel of the color image in YCbCr space is decomposed by RIDWT, the lowest frequency sub-band is divided into non-overlapping blocks. Blocks with a lower standard deviation are selected to embed each bit of the watermark created from the iris image into a block. Watermarking of selected blocks is performed with QR decomposition in the first approach and Schur decomposition in the second approach. The firefly algorithm is used to balance the robustness and perceptual transparency in hiding the watermark. Experimental results are evaluated in terms of robustness and imperceptibility to prove the effectiveness of the proposed systems. In addition, validation performances are analyzed based on false rejection rate, false acceptance rate and equal error rate. The results show that both methods have high perceptual quality and robustness, and also a very low error rate in ownership verification.

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“…Nazari and Mehrabian (2021) introduced a secure blind watermarking algorithm based on integer wavelet transform (IWT), least significant bit (LSB), and chaotic sequence (iterative learning control, ILC) to increase the capacity and security of watermark embedment. Agarwal et al (2015) combined watermarking and biometrics to improve owner identification/verification techniques based on discrete wavelet transform (DWT), and proposed and compared four blind invisible watermarking approaches based on face images and wavelets. The four methods offer respective advantages for different types of attacks.…”

Section: Introductionmentioning

confidence: 99%

Strong Robustness Watermarking Algorithm Based on Lifting Wavelet Transform and Hessenberg Decomposition

Lin

Wang

et al. 2022

International Journal of Web Services Research

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Watermark imperceptibility and robustness in the present watermarking algorithm based on discrete wavelet transform (DWT) could be weakened due to data truncation. To solve this problem, a strong robustness watermarking algorithm based on the lifting wavelet transform is proposed. First, the color channels of the original image are separated, and the selected channels are processed through lifting wavelet transform to obtain low-frequency information. The information is then split into blocks, with Hesseneberg decomposition performed on each block. Arnold algorithm is used to scramble the watermark image, and the scrambled watermark is transformed into a binary sequence that is then embedded into the maximum element of Hessenberg decomposed matrix by quantization modulation. The experimental results exhibit a good robustness of this new algorithm in defending against a wide variety of conventional attacks.

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Blind reliable invisible watermarking method in wavelet domain for face image watermark

Cited by 25 publications

References 62 publications

A Digital Image Watermarking System: An Application of Dual Layer Watermarking Technique

A Digital Image Watermarking System: An Application of Dual Layer Watermarking Technique

Biometric Watermarking Schemes Based on QR Decomposition and Schur Decompositon in RIDWT Domain

Strong Robustness Watermarking Algorithm Based on Lifting Wavelet Transform and Hessenberg Decomposition

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