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A Semi-fragile Watermarking Tolerant of Laplacian Sharpening

Authors: Jun Xiao 0005; Ying Wang 0030;

A Semi-fragile Watermarking Tolerant of Laplacian Sharpening

Abstract

Semi-fragile watermarking technique which aims to discriminate malicious manipulations from admissible manipulations, is drawing many attentions in image authentication. In this paper, a novel semi-fragile image watermarking algorithm that accepts Laplacian sharpening is proposed. In the proposed algorithm, based on the theory of Laplacian sharpening, the watermark is embedded in the space domain by modifying the parity of the pixel value and its Laplacian sharpening result, so it has very low complexity and high fidelity. The robustness and frangibility of the proposed algorithm to given image processes are analyzed theoretically and experimentally, and the results show that the proposed algorithm can tolerate Laplacian sharpening very well, while it is very fragile to other attacks, such as Gauss noise, cropping, neighborhood averaging and median filter. Namely, the proposed algorithm can distinguish Laplacian sharpening from other attacks accurately.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Top 10%
Average
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