The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article se concentre sur le système de filigrane utilisant un processus de quantification contrôlée. Nous présentons d’abord un modèle des processus d’incorporation et d’extraction de filigrane et effectuons leurs analyses. Ensuite, nous examinons la robustesse du système de tatouage par rapport au traitement d'image courant et clarifions la raison pour laquelle des erreurs de détection se produisent dans le processus d'extraction du filigrane. Sur la base du résultat, nous améliorons le processus d’extraction des filigranes et concevons des systèmes de filigrane robustes. L'amélioration est réalisée à l'aide d'un filtre de déconvolution et de techniques de réseau neuronal. Les expériences numériques utilisant le système de filigrane basé sur DCT montrent les bonnes performances que nous attendions.
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Akio MIYAZAKI, Akihiro OKAMOTO, "Analysis of Watermarking Systems in the Frequency Domain and Its Application to Design of Robust Watermarking Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 1, pp. 117-124, January 2002, doi: .
Abstract: This paper focuses on the watermarking system using a controlled quantization process. We first present a model of the watermark embedding and extracting processes and carry out their analyses. Then we examine the robustness of the watermarking system against common image processing and clarify the reason why detection errors occur in the watermark extracting process. Based on the result, we improve the watermark extracting process and design robust watermarking systems. The improvement is accomplished using a deconvolution filter and neural network techniques. Numerical experiments using the DCT-based watermarking system show good performance as expected by us.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_1_117/_p
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@ARTICLE{e85-a_1_117,
author={Akio MIYAZAKI, Akihiro OKAMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Analysis of Watermarking Systems in the Frequency Domain and Its Application to Design of Robust Watermarking Systems},
year={2002},
volume={E85-A},
number={1},
pages={117-124},
abstract={This paper focuses on the watermarking system using a controlled quantization process. We first present a model of the watermark embedding and extracting processes and carry out their analyses. Then we examine the robustness of the watermarking system against common image processing and clarify the reason why detection errors occur in the watermark extracting process. Based on the result, we improve the watermark extracting process and design robust watermarking systems. The improvement is accomplished using a deconvolution filter and neural network techniques. Numerical experiments using the DCT-based watermarking system show good performance as expected by us.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Analysis of Watermarking Systems in the Frequency Domain and Its Application to Design of Robust Watermarking Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 117
EP - 124
AU - Akio MIYAZAKI
AU - Akihiro OKAMOTO
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2002
AB - This paper focuses on the watermarking system using a controlled quantization process. We first present a model of the watermark embedding and extracting processes and carry out their analyses. Then we examine the robustness of the watermarking system against common image processing and clarify the reason why detection errors occur in the watermark extracting process. Based on the result, we improve the watermark extracting process and design robust watermarking systems. The improvement is accomplished using a deconvolution filter and neural network techniques. Numerical experiments using the DCT-based watermarking system show good performance as expected by us.
ER -