基于冗余剩余数系统和混沌的医学图像鲁棒脆弱水印

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
M. T. Naseem, I. Qureshi, Atta-ur-Rahman, M. Z. Muzaffar
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引用次数: 4

摘要

研究了一种利用冗余剩余数系统和混沌的新型水印方案。该方法的显著特点是在保证水印信息鲁棒性的同时保持图像的脆弱性。图像像素被转换成残差,使人眼无法看到图像内容。为了使图像肉眼不可见,只对图像的ROI部分进行残差数处理,从而增强了图像的保密性。在将图像的感兴趣部分转换为残差的过程中,由于残差超过8位,因此通过相应的智能机制将残差转换为精确的8位。为了实现水印的鲁棒性,首先对水印进行冗余残差处理,然后对生成的水印进行纠错编码。为了实现图像的脆弱性,利用了哈希技术。为了提高水印的安全性,将带有剩余感兴趣点的整个图像的哈希值与经过编码的冗余剩余水印相结合,然后将生成的水印嵌入混沌密钥根上的原生图像的非感兴趣区域(RONI)中。在不被篡改的情况下,可以成功地恢复脆弱水印并精确地恢复原始图像,但如果图像受到攻击,脆弱水印将被破坏,而提取出可读性更好的鲁棒水印。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust and fragile watermarking for medical images using redundant residue number system and chaos
This research discusses a novel watermarking scheme using redundant residue number system and chaos. The salient feature of said research is that image remains fragile while the watermark information is made robust. Image pixels are converted into residues so that the unaided eye could not see the image contents. To make the image invisible to the unaided eye, only the ROI part of image is passed through the Residue Number System thus, to enhance the secrecy of the image. While converting the ROI part of image into residues, there are some residues which exceed eight bits so, these residues are converted to exact eight bits by pertaining some intelligent mechanism. To achieve the robustness of watermark, firstly redundant residues of watermark are made and then the resultant watermark is encoded through error correcting codes. To achieve the fragility of image, hashing technique is utilized. Hash of the entire image but with the residued ROI is combined with the encoded and redundant residued watermark and then resultant watermark is embedded in the Region of non-interest (RONI) zone of native image rooted on the chaotic key in order to enhance the security of the watermark. In case of no tampering, fragile watermark can be successfully recovered as well as exact recovery of the original image but if the image is attacked, the fragile watermark is destroyed while the robust watermark is extracted with better readability.
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来源期刊
Neural Network World
Neural Network World 工程技术-计算机:人工智能
CiteScore
1.80
自引率
0.00%
发文量
0
审稿时长
12 months
期刊介绍: Neural Network World is a bimonthly journal providing the latest developments in the field of informatics with attention mainly devoted to the problems of: brain science, theory and applications of neural networks (both artificial and natural), fuzzy-neural systems, methods and applications of evolutionary algorithms, methods of parallel and mass-parallel computing, problems of soft-computing, methods of artificial intelligence.
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