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High capacity data hiding scheme based on (7, 4) Hamming code

Aiming to embed large amount of data while minimize the sum of costs of all changed pixels, a novel high capacity data hiding scheme based on (7, 4) Hamming code is realized by a family of algorithms. Firstly, n (n = 1, 2, 3) cover pixels are assigned to one set according to the payload. Then, 128 b...

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Detalles Bibliográficos
Autores principales: Cao, Zekun, Yin, Zhaoxia, Hu, Honghe, Gao, Xiangping, Wang, Liangmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766181/
https://www.ncbi.nlm.nih.gov/pubmed/27026872
http://dx.doi.org/10.1186/s40064-016-1818-0
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author Cao, Zekun
Yin, Zhaoxia
Hu, Honghe
Gao, Xiangping
Wang, Liangmin
author_facet Cao, Zekun
Yin, Zhaoxia
Hu, Honghe
Gao, Xiangping
Wang, Liangmin
author_sort Cao, Zekun
collection PubMed
description Aiming to embed large amount of data while minimize the sum of costs of all changed pixels, a novel high capacity data hiding scheme based on (7, 4) Hamming code is realized by a family of algorithms. Firstly, n (n = 1, 2, 3) cover pixels are assigned to one set according to the payload. Then, 128 binary strings of length seven are divided into eight sets according to the syndrome of every binary string. Binary strings that share the same syndrome are classified into one set. Finally, a binary string in a certain set determined by the data to be embedded is chosen to modify some of the least significant bits of the n cover pixels. The experimental results demonstrate that the image quality of the proposed method with high embedding payload is superior to those of the related schemes.
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spelling pubmed-47661812016-03-29 High capacity data hiding scheme based on (7, 4) Hamming code Cao, Zekun Yin, Zhaoxia Hu, Honghe Gao, Xiangping Wang, Liangmin Springerplus Research Aiming to embed large amount of data while minimize the sum of costs of all changed pixels, a novel high capacity data hiding scheme based on (7, 4) Hamming code is realized by a family of algorithms. Firstly, n (n = 1, 2, 3) cover pixels are assigned to one set according to the payload. Then, 128 binary strings of length seven are divided into eight sets according to the syndrome of every binary string. Binary strings that share the same syndrome are classified into one set. Finally, a binary string in a certain set determined by the data to be embedded is chosen to modify some of the least significant bits of the n cover pixels. The experimental results demonstrate that the image quality of the proposed method with high embedding payload is superior to those of the related schemes. Springer International Publishing 2016-02-25 /pmc/articles/PMC4766181/ /pubmed/27026872 http://dx.doi.org/10.1186/s40064-016-1818-0 Text en © Cao et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Cao, Zekun
Yin, Zhaoxia
Hu, Honghe
Gao, Xiangping
Wang, Liangmin
High capacity data hiding scheme based on (7, 4) Hamming code
title High capacity data hiding scheme based on (7, 4) Hamming code
title_full High capacity data hiding scheme based on (7, 4) Hamming code
title_fullStr High capacity data hiding scheme based on (7, 4) Hamming code
title_full_unstemmed High capacity data hiding scheme based on (7, 4) Hamming code
title_short High capacity data hiding scheme based on (7, 4) Hamming code
title_sort high capacity data hiding scheme based on (7, 4) hamming code
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766181/
https://www.ncbi.nlm.nih.gov/pubmed/27026872
http://dx.doi.org/10.1186/s40064-016-1818-0
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