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Secret image sharing using (t,n) threshold scheme with lossless recovery

Authors: Ming-Chun Chien; Jen-Ing G. Hwang;

Secret image sharing using (t,n) threshold scheme with lossless recovery

Abstract

Secret image sharing is a means of hiding an image within another image to generate similar images. In 1979, Shamir proposed a method of secret image sharing known as the (t, n) threshold scheme. (t, n) threshold schemes can generate n shadow images and any t of n shadow images can be used to reconstruct the secret image and cover image. Secret image sharing has two main parts: secret image sharing and secret image recovery. The goal of sharing is to embed a secret image in a cover image and reduce the distortion of the shadow image. The most important aspect of recovery is reconstructing the secret image with lossless. Many current schemes perform well at the first task, but most fail to recover the secret image successfully. To address this problem, we propose a novel method for secret image sharing based on a power-of-two Galois field rather than primes. Our experimental results showed that our scheme delivered satisfactory quality shadow images, while it could reconstruct secret images and cover images successfully with lossless.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
10
Average
Top 10%
Average
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