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AuSR1: Authentication and self-recovery using a new image inpainting technique with LSB shifting in fragile image watermarking
被引:31
作者:
Aminuddin, Afrig
[1
]
Ernawan, Ferda
[2
,3
]
机构:
[1] Univ Amikom, Fac Comp Sci, Dept Informat, Yogyakarta, Indonesia
[2] Univ Malaysia Pahang, Coll Comp & Appl Sci, Fac Comp, Dept Comp G & Multimedia, Kuantan, Malaysia
[3] Univ Malaysia Pahang, Coll Comp & Appl Sci, Fac Comp, Kuantan 26600, Malaysia
关键词:
Blind fragile watermarking;
Self-embedding;
Image authentication;
Self-recovery;
Image inpainting;
EMBEDDING WATERMARKING;
TAMPERING DETECTION;
SCHEME;
LOCALIZATION;
TRANSFORM;
ALGORITHM;
SELECTION;
D O I:
10.1016/j.jksuci.2022.02.009
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
With the rapid development of multimedia technology, editing and manipulating digital images have become more accessible than ever. This paper proposed color image authentication based on blind fragile image watermarking for tamper detection and self-recovery named AuSR1. The AuSR1 divides each chan-nel of the cover image into non-overlapping blocks with the size of 2 x 2 pixels. The authentication data is embedded into the original block location, while the recovery data is embedded into the distant loca-tion from the original location based on the block mapping algorithm. The watermark data is then embedded into the 2 LSB to achieve high quality of the recovered image under tampering attacks. In addi-tion, the permutation algorithm is applied to ensure the security of the watermark data. The AuSR1 uti-lizes a three-layer authentication algorithm to achieve a high detection rate. The experimental results show that the scheme produced a PSNR value of 45.57 dB and an SSIM value of 0.9972 of the water-marked images. Furthermore, the AuSR1 detected the tampered area of the images with a high precision value of 0.9943. In addition, the recovered image achieved a PSNR value of 27.64 dB and an SSIM value of 0.9339 on a 50% tampering rate.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页码:5822 / 5840
页数:19
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