AI-assisted deepfake detection using adaptive blind image watermarking

Hsu, Ling-Yuan

doi:10.1016/j.jvcir.2024.104094

Cited by 1 publication

(1 citation statement)

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“…The cover image is divided into blocks, each block is transformed by wavelet transform as the carrier signal, and two different chaotic maps are used for encryption, which improves the security of the watermark image. Hsu et al [14] proposed a new adaptive blind watermarking technique for deep forgery detection. This technique embeds the deep forgery detection information into the image, extracts the image without additional information and verifies the authenticity of the image.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Domain Color Image Watermarking Scheme Based on Hyperchaotic Mapping

Dong,

Yan,

Zhang

et al. 2024

Mathematics

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In the field of image watermarking technology, it is very important to balance imperceptibility, robustness and embedding capacity. In order to solve this key problem, this paper proposes a new color image adaptive watermarking scheme based on discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD). In order to improve the security of the watermark, we use Lorenz hyperchaotic mapping to encrypt the watermark image. We adaptively determine the embedding factor by calculating the Bhattacharyya distance between the cover image and the watermark image, and combine the Alpha blending technique to embed the watermark image into the Y component of the YCbCr color space to enhance the imperceptibility of the algorithm. The experimental results show that the average PSNR of our scheme is 45.9382 dB, and the SSIM is 0.9986. Through a large number of experimental results and comparative analysis, it shows that the scheme has good imperceptibility and robustness, indicating that we have achieved a good balance between imperceptibility, robustness and embedding capacity.

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Section: Introductionmentioning

confidence: 99%