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Efficient constructions for progressive visual cryptography with meaningful shares

机译:具有有意义份额的渐进式视觉密码的有效构造

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In a progressive visual cryptography scheme (PVCS), the clarity of recovered images can be enhanced by increasing the number of stacking shares. Noise-like shares are hard to identify, therefore, user-friendly progressive visual cryptography schemes (FPVCSs) generate meaningful shares. This paper proposes two encryption approaches to construct FPVCSs. One is a general OR-based FPVCS called (2, n)-FPVCS, and the other is an XOR-based FPVCS called (2, n)-XFPVCS. The common issues of the two models include: (1) systematic approaches, (2) avoiding the pixel-expansion, (3) providing adjustable visual quality of meaningful shares, and (4) eliminating residual traces of cover images. Moreover, the paper theoretically analyzes and carries out experiments to verify the visual qualities of the proposed two models. The experiment results indicate that the proposed approaches can accomplish these objectives simultaneously. In addition, (2,n)-FPVCS can adjust the threshold of trace-elimination by setting a parameter, which improves the flexibility of the proposed approach. As well as (2, n)-XFPVCS obtains a fully decrypted final recovered image. (C) 2019 Elsevier B.V. All rights reserved.
机译:在渐进式视觉加密方案(PVCS)中,可以通过增加堆叠份额的数量来增强恢复图像的清晰度。类似噪声的份额很难识别,因此,用户友好的渐进式视觉加密方案(FPVCS)会产生有意义的份额。本文提出了两种加密方法来构造FPVCS。一个是基于常规OR的FPVCS,称为(2,n)-FPVCS,另一个是基于XOR的FPVCS,称为(2,n)-XFPVCS。这两个模型的共同问题包括:(1)系统方法,(2)避免像素扩展,(3)提供有意义份额的可调视觉质量,以及(4)消除封面图像的残留痕迹。此外,本文从理论上分析并进行了实验,以验证所提出的两个模型的视觉质量。实验结果表明,所提出的方法可以同时完成这些目标。另外,(2,n)-FPVCS可以通过设置参数来调整痕量消除阈值,从而提高了所提出方法的灵活性。以及(2,n)-XFPVCS也获得了完全解密的最终恢复图像。 (C)2019 Elsevier B.V.保留所有权利。

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