<title>Quantization-based semi-fragile public-key watermarking for secure image authentication</title>

Abstract

Authentication watermarking approaches can be classified into two kinds: fragile and semi-fragile. In contrast to the latter one, fragile watermarking does not tolerate modifications of any single bit of the watermarked data. Since the transmission of digital data often requires lossy compression, an authentication system should accept non-malicious modifications such as JPEG compression. Semi-fragile techniques aim to discriminate malicious manipulations from admissible manipulations. In our approach, we extract image content dependent information, which is hashed afterwards and encrypted using secure methods known from the classical cryptography. The image data is partitioned into nonoverlapping 4 x 4 pixel blocks in the spatial domain. The mean values of these blocks form n-dimensional vectors, which are quantized to the nearest lattice point neighbours. Based on the changed vector values, a hash is calculated and asymmetrically encrypted, resulting in a digital signature. Traditional dual subspace approaches divide the signal space into a region for signature generation and a region for signature embedding. To ensure the security of the whole image, we join the two subspaces. The vectors, where to embed the bits using quantization-based data hiding techniques, are predistorted and also used for the signature generation. Our scheme applies error correction coding to gain the robustness of the embedded signature to non-malicious distortions. A second quantization run finally embeds the signature.

Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images

“…For semi-fragile watermarking algorithms in spatial domains, the pixels of digital images are processed directly to achieve the purpose of embedding watermarking information [10][11][12][13][14]. For example, some algorithms embed the watermarking information into the least significant bit (LSB) in the image pixels directly [11,12].…”

“…Although the spatial domain algorithms can be implemented easily, it is difficult to balance the invisibility and robustness of the watermark. Schlauweg et al [10] proposed an authentication algorithm combining multidimensional dither modulation with error-correction coding. By using lattice quantization, the watermarking information associated with the image content is generated by all the pixel values in the image.…”

Dual watermarking for protection of rightful ownership and secure image authentication

“…We suggested creating a gap around this threshold to tolerate slight changes due to compression. Further, a mapping process was presented that allows using a quantization-based watermark embedding approach [9] to hide information within the host video frame. The structure of the quantization lattice is self-adapting depending on L x and L y .…”

“…Therefore, every wavelet coefficient w of the transformed image is quantized to an invariant value, which is not changed during the signature embedding process [9]. Except for the dead-zone, the magnitude of every coefficient is set to the centre of the according δ-sized hash interval, in Figure 9 marked with the symbols .…”

“…The aim is to allow admissible manipulations such as JPEG compression, but to reject malicious manipulations that change the visual content. Commonly used techniques extract features representing the image content and re-embed these features as watermark information into the host image data [3], [4], [7][8][9][10][11][12]. Some approaches involve image positions of edges, contours or zerocrossings in the spatial domain whose existence is proved during the verification process.…”