基于三角剖分的数字图像分存算法

doi:10.11896/j.issn.1002-137X.2019.04.020

摘要/Abstract

摘要： 网络的不安全性导致图像信息在传输过程中容易丢失、损坏,或被不法分子窃取并用于非法传输,因此,研究数字图像的加密技术可以有效加强图像信息的安全性。数字图像分存算法是一种重要的图像信息加密技术,但是以往的图像分存技术没有考虑像素灰度分布特征,对图像进行逐像素加密,既降低了安全性,也产生了不必要的时空开销。为此,文中采用了基于数字图像像素灰度特征的非均匀三角剖分算法,结合门限方案,提出了一种新的数字图像分存算法。首先,使用非均匀三角网格剖分算法,得到随图像灰度值变化的剖分网格;其次,使用门限方案对剖分网格中每一个子三角形的顶点像素进行加密和共享;最后,使用拉格朗日插值多项式和剖分网格编码信息重构出原始图像。实验结果表明,该方法降低了像素的冗余加密,提高了安全性且图像重构效果较好,是一种有效的图像分存算法。

关键词: 门限方案, 三角剖分, 图像分存

Abstract: The digital image is easily lost,damaged,and stolen by cheaters and used for illegal transmission because of the insecure network.Therefore,the digital image encryption technology can effectively enhance the security of image.The digital image sharing algorithm is an important encryption technology.However,the conventional image sharing technologiesrepeat encryption pixel by pixel without considering the gray distribution characteristic,resulting in both reduced security and unnecessary space-time overhead.To handle the above problems,a new digital image sharing algorithm was proposed by adopting the gray distribution characteristic based non-uniform triangular partition algorithm and the threshold scheme.First,the non-uniform triangular partition algorithm is used to obtain the mesh of the image according to the gray distribution characteristic.Second,the threshold scheme is used to encrypt and share the vertex pixels of each sub-triangle in the mesh.Finally,the original image is reconstructed by using the Lagrange interpolation polynomial and the mesh coding information.The experimental results show that the proposed method reduces the redundant encryption of pixels,improves the security and has good image reconstruction effect,so it is an effective image sharing algorithm.

Key words: Image sharing, Threshold scheme, Triangular partition

中图分类号:

TP391.41

袁茜茜, 蔡占川. 基于三角剖分的数字图像分存算法[J]. 计算机科学, 2019, 46(4): 123-128. https://doi.org/10.11896/j.issn.1002-137X.2019.04.020

YUAN Xi-xi, CAI Zhan-chuan. Digital Image Sharing Algorithm Based on Triangular Partition[J]. Computer Science, 2019, 46(4): 123-128. https://doi.org/10.11896/j.issn.1002-137X.2019.04.020

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