Affine Invariant Watermark Scheme using Genetic Algorithm

Detalhes bibliográficos
Autor(a) principal: Cong, Jin
Data de Publicação: 2005
Outros Autores: Peng, Jiaxiong
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/108
Resumo: Geometrical attacks are among the most challenging problems in present day digital watermark. Such attacks are very simple to implement yet they can defeat most of the existing digital watermark algorithms without causing serious perceptual image distortion. Geometric attacks can very easily confuse the decoder unless it transforms the image back to its original size/orientation, i.e., recover the lost synchronism. To be able do so, the decoder needs to know how the image has been manipulated, i.e., needs to know geometric transformation parameters. In this research, we report a novel method to estimate the geometric manipulation. We compute the point pattern matching measure for the geometric manipulation. The shape-specific points of the original image are computed. The point matching is realized by genetic algorithm. The proposed scheme does not require the original image because SSP information of the original image has been memorized by the neural network. This method has been proved its robustness to geometric attacks through experiments.
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spelling Affine Invariant Watermark Scheme using Genetic Algorithmgeometrical transformationshape-specific pointspoints matchinggenetic algorithmneural networkGeometrical attacks are among the most challenging problems in present day digital watermark. Such attacks are very simple to implement yet they can defeat most of the existing digital watermark algorithms without causing serious perceptual image distortion. Geometric attacks can very easily confuse the decoder unless it transforms the image back to its original size/orientation, i.e., recover the lost synchronism. To be able do so, the decoder needs to know how the image has been manipulated, i.e., needs to know geometric transformation parameters. In this research, we report a novel method to estimate the geometric manipulation. We compute the point pattern matching measure for the geometric manipulation. The shape-specific points of the original image are computed. The point matching is realized by genetic algorithm. The proposed scheme does not require the original image because SSP information of the original image has been memorized by the neural network. This method has been proved its robustness to geometric attacks through experiments.Editora da UFLA2005-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/108INFOCOMP Journal of Computer Science; Vol. 4 No. 4 (2005): December, 2005; 20-261982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/108/93Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessCong, JinPeng, Jiaxiong2015-06-22T12:47:09Zoai:infocomp.dcc.ufla.br:article/108Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:17.638561INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Affine Invariant Watermark Scheme using Genetic Algorithm
title Affine Invariant Watermark Scheme using Genetic Algorithm
spellingShingle Affine Invariant Watermark Scheme using Genetic Algorithm
Cong, Jin
geometrical transformation
shape-specific points
points matching
genetic algorithm
neural network
title_short Affine Invariant Watermark Scheme using Genetic Algorithm
title_full Affine Invariant Watermark Scheme using Genetic Algorithm
title_fullStr Affine Invariant Watermark Scheme using Genetic Algorithm
title_full_unstemmed Affine Invariant Watermark Scheme using Genetic Algorithm
title_sort Affine Invariant Watermark Scheme using Genetic Algorithm
author Cong, Jin
author_facet Cong, Jin
Peng, Jiaxiong
author_role author
author2 Peng, Jiaxiong
author2_role author
dc.contributor.author.fl_str_mv Cong, Jin
Peng, Jiaxiong
dc.subject.por.fl_str_mv geometrical transformation
shape-specific points
points matching
genetic algorithm
neural network
topic geometrical transformation
shape-specific points
points matching
genetic algorithm
neural network
description Geometrical attacks are among the most challenging problems in present day digital watermark. Such attacks are very simple to implement yet they can defeat most of the existing digital watermark algorithms without causing serious perceptual image distortion. Geometric attacks can very easily confuse the decoder unless it transforms the image back to its original size/orientation, i.e., recover the lost synchronism. To be able do so, the decoder needs to know how the image has been manipulated, i.e., needs to know geometric transformation parameters. In this research, we report a novel method to estimate the geometric manipulation. We compute the point pattern matching measure for the geometric manipulation. The shape-specific points of the original image are computed. The point matching is realized by genetic algorithm. The proposed scheme does not require the original image because SSP information of the original image has been memorized by the neural network. This method has been proved its robustness to geometric attacks through experiments.
publishDate 2005
dc.date.none.fl_str_mv 2005-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/108
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/108
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/108/93
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 4 No. 4 (2005): December, 2005; 20-26
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
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