Quadri-directional searching algorithm for secret image sharing using meaningful shadows

Huynh, Ngoc-Tu; Bharanitharan, K.; Chang, Chin‐Chen

doi:10.1016/j.jvcir.2015.01.011

Cited by 25 publications

(1 citation statement)

References 17 publications

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“…Shortly after [21] was published, an updated version of it was put forward that not only enhanced visual quality, but also had a larger capacity for embedded secret data [22]. Subsequently, a low computational complexity Quadri-Directional Searching Algorithm (QDSA) for secret image sharing was proposed [23], thereby enabling the modification of the original cover pixel values to be limited within a small range according to the value of ω. Moreover, the shadow images can achieve excellent visual quality, as demonstrated by [24], followed by a (2, 2)-threshold reversible IH-VSS scheme that achieve high quality and have authentication ability by skillfully employing a turtle shell matrix [25].…”

Section: Introductionmentioning

confidence: 99%

Using Two Meaningful Shadows to Share Secret Messages with Reversibility

Lin

Chang

2019

Symmetry

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A subtopic of visual secret sharing (VSS) is information hiding-based VSS (IH-VSS), which embeds secret messages into images using an information hiding technique. In the IH-VSS scheme, stego-images are divided into shadows under the guidance and constraint of some predetermined approaches. In order to achieve the purpose of security and reliability, the hidden information cannot be recovered unless a certain amount or all of the credible shadows work together. In this paper, we propose a (2, 2) IH-VSS scheme with reversibility and friendliness. In the shadow generation phase, two meaningful shadow images are produced and then distributed. In the extraction and restoration phase, the hidden secret information and cover image, respectively, can be reconstructed credibly and correctly. No complex computation of shadow generation is involved, but high security is achieved. Moreover, a satisfying peak-signal-to-noise ratio (PSNR) is obtained with the high embedding capacity of 1.59 bpp in a very simple and effective way.

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