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Coverless Image Information Hiding Based on Deep Convolution Features

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成果类型:
会议论文
作者:
Qin J.;Wang J.;Sun J.;Xiang X.;Xiang L.
通讯作者:
Qin, J.
作者机构:
Hunan Applied Technology University, Changde, Hunan, 415000, China
[Xiang L.; Wang J.; Xiang X.] College of Computer Science and Information Technology, Central South University of Forestry and Technology, Changsha, 410004, China
[Sun J.; Qin J.] Hunan Applied Technology University, Changde, Hunan, 415000, China, College of Computer Science and Information Technology, Central South University of Forestry and Technology, Changsha, 410004, China
通讯机构:
[Qin, J.] H
Hunan Applied Technology UniversityChina
语种:
英文
关键词:
Coverless image hiding;Deep CNN;Deep learning;Hash
期刊:
Communications in Computer and Information Science
ISSN:
1865-0929
年:
2021
卷:
1494 CCIS
页码:
15-30
会议名称:
39th National Conference of Theoretical Computer Science, NCTCS 2021
会议时间:
23 July 2021 through 25 July 2021
主编:
Cai Z.Li J.Zhang J.
出版者:
Springer Science and Business Media Deutschland GmbH
ISBN:
9789811674426
基金类别:
Acknowledgement. The author would like to thank the support of Central South University of Forestry & Technology and the support of National Science Fund of China.
机构署名:
本校为其他机构
院系归属:
计算机与信息工程学院
摘要:
The coverless information hiding technology proposed in recent years does not need to modify the carrier image and has good anti-detection ability. However, the existing coverless information hiding technology has the problems of low hiding capacity and poor robustness. To solve this problem, this paper proposed a coverless image information hiding algorithm based on deep convolution feature, which mainly constructs the mapping relationship between image feature and secret information through deep convolution neural network to realize covert co...

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