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.
This paper deals with the efficient storage and transmission of stereo images. It introduces a compression algorithm based on the Discrete Wavelet Transform and an adapted SPIHT-coder. By using objective quality tests, it is shown that this coder is superior to all other coders published so far.
The gastronomy sector was one of the industries most fundamentally affected by the COVID-19 pandemic restrictions and the subsequent disruption of demand. Entrepreneurs were challenged to secure their survival. This study aims to analyze how COVID-19 has accelerated digital technologies in the hospitality industry. The study assumes that due to lockdowns successful restaurants in Baden–Wuerttemberg have developed new digital business models. Data for the quantitative study were collected through a survey among randomly selected restaurants carried out between December 2020 and February 2021. A cluster analysis is used to identify different types of restaurants concerning their propensity to innovate and their success. Results of the study show that the level of digitization is one important factor regarding the range of entrepreneurial success.
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