Fragile Watermarking for Image Authentication Using QR factorization and Fourier Transform

Nejati, Fatemeh; Sajedi, Hedieh; Mohammadi, Maryam

doi:10.1109/icwr.2019.8765292

Cited by 6 publications

(2 citation statements)

References 15 publications

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“…The most widely used instruments to measure imperceptibility quality are PSNR and SSIM [13]. Fragile image watermarking can be designed in the spatial domain as in research [11,[14][15][16] or transformation domain [1,17,18] or these combination [2,19,20]. Determination of methods and domains can influence the results and advantages of the method in certain aspects.…”

Section: Introductionmentioning

confidence: 99%

Fragile Image Watermarking Based on Bidiagonal SVD-LSB for Tamper Detection and Localization

2022

IJIES

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Tamper detection and localization are essential things in fragile image watermarking to carry out the authentication process. The tampering method continues to evolve from general and complex tampering. This study proposes a tamper detection and localization technique that can withstand a variety of standard and complex attacks with a combination of bidiagonal singular value decomposition, blockwise and group block for authentication. The least significant bit method is used in the embedding process to increase imperceptibility. By combining these methods, fragile image watermarking is produced that is robust against various common tampers such as type I and type II copypaste, rotate, text addition, and noise addition, as well as various complex attacks such as vector quantization, collage, content only and constant feature. The tamper detection rate is more than 0.99, and the average PSNR value is 51.85 dB. This shows that the proposed method is robust against various tampers and has excellent imperceptibility.

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Section: Introductionmentioning

confidence: 99%

Fragile Image Watermarking Based on Bidiagonal SVD-LSB for Tamper Detection and Localization

2022

IJIES

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“…Until recently, digital watermarking was based on deterministic algorithms. Typical methods are based on embedding the watermark in one of the discrete cosine transform (DCT) [3], discrete wavelet transform (DWT) [4][5][6], discrete Fourier transform (DFT) [7], or quantization index modulation [8], or a combination of these [9,10].…”

Section: Introductionmentioning

confidence: 99%

Convolutional Neural Network-Based Image Watermarking using Discrete Wavelet Transform

Tavakoli¹,

Honjani²,

Sajedi³

2022

Preprint

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With the growing popularity of the Internet, digital images are used and transferred more frequently. Although this phenomenon facilitates easy access to information, it also creates security concerns and violates intellectual property rights by allowing illegal use, copying, and digital content theft. Using watermarks in digital images is one of the most common ways to maintain security. Watermarking is proving and declaring ownership of an image by adding a digital watermark to the original image. Watermarks can be either text or an image placed overtly or covertly in an image and are expected to be challenging to remove. This paper proposes a combination of convolutional neural networks (CNNs) and wavelet transforms to obtain a watermarking network for embedding and extracting watermarks. The network is independent of the host image resolution, can accept all kinds of watermarks, and has only 11 layers while keeping performance. Performance is measured by two terms; the similarity between the extracted watermark and the original one and the similarity between the host image and the watermarked one.

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Optical fragile watermarking based on single-pixel ptychography and variational image decomposition

Su,

Zhang,

Zhao

et al. 2024

Opt Quant Electron

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Fragile Watermarking for Image Authentication Using QR factorization and Fourier Transform

Cited by 6 publications

References 15 publications

Fragile Image Watermarking Based on Bidiagonal SVD-LSB for Tamper Detection and Localization

Fragile Image Watermarking Based on Bidiagonal SVD-LSB for Tamper Detection and Localization

Convolutional Neural Network-Based Image Watermarking using Discrete Wavelet Transform

Optical fragile watermarking based on single-pixel ptychography and variational image decomposition

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