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Multi-tone Watermark Hiding in Halftone Images

Authors: Guo, J; Liu, Y;

Multi-tone Watermark Hiding in Halftone Images

Abstract

This work presents a method with a low computational complexity to embed a multi-tone watermark. A halftone image is obtained using regular error diffusion, while the other image is obtained using the proposed Generalized Noise-Balanced Error Diffusion (GNBEDF) when, simultaneously, considering the properties of the watermark and the first halftone image. The proposed method makes the bi-level watermarking becomes a special case to multi-tone watermarking. The bi-level watermark decoding can be achieved via printing the two halftone images onto two transparencies, then superimposing them together to reveal the watermark pattern. However, given that the multi-tone watermark is involved, the proposed Gaussian Difference (GD) approach is required to perform the decoding to produce a decoded multi-tone watermark. Moreover, the Single Image Decodable GNBEDF (SID-GNBEDF) is also proposed for the case where only one embedded image is available in the decoder. A lowpass filter obtained by Least-Mean-Square is employed throughout this study to assess the image quality. As demonstrated in experimental results, the proposed approach can guard again reasonable attacks (cropping and print-and-scan).

Keywords

B.4.2.c Image display, Decoding, E.4.a Data compaction and compression, D.4.6.b Authentication, Gaussian processes, I.4 Image Processing and Computer Vision, I.4.2.e Video coding, Computational complexity, H.2 Database Management, H.3 Information Storage and Retrieval, D.2.11.c Information hiding, H.5.1.g Video, Data mining, I.4.0.a Image displays

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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!
0
Average
Average
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