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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cette lettre, nous proposons un algorithme de détection robuste pour le filigrane audio pour la protection des droits d'auteur. Le filigrane est intégré dans le domaine temporel d'un signal audio par la technique d'étalement du spectre normalement utilisée. Le schéma de détection est une amélioration du détecteur de corrélation conventionnel. Un filtre passe-haut est appliqué avec le filtre d'erreur de prédiction linéaire pour blanchir le signal audio et un seuil adaptatif est choisi pour la comparaison des décisions. Les résultats expérimentaux montrent que notre algorithme de détection surpasse l'algorithme conventionnel non seulement parce qu'il améliore la robustesse aux attaques normales, mais également parce qu'il peut fournir la robustesse à la modification de l'échelle de hauteur invariante dans le temps.
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Lili LI, Xiangzhong FANG, "Robust Detection Algorithm for Spread Spectrum Audio Watermarking" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 11, pp. 3389-3392, November 2008, doi: 10.1093/ietfec/e91-a.11.3389.
Abstract: In this letter we propose a robust detection algorithm for audio watermarking for copyright protection. The watermark is embedded in the time domain of an audio signal by the normally used spread spectrum technique. The scheme of detection is an improvement of the conventional correlation detector. A high-pass filter is applied along with the linear prediction error filter for whitening the audio signal and an adaptive threshold is chosen for decision comparing. Experimental results show that our detection algorithm outperforms the conventional one not only because it improves the robustness to normal attacks but also because it can provide the robustness to time-invariant pitch-scale modification.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.11.3389/_p
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@ARTICLE{e91-a_11_3389,
author={Lili LI, Xiangzhong FANG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Robust Detection Algorithm for Spread Spectrum Audio Watermarking},
year={2008},
volume={E91-A},
number={11},
pages={3389-3392},
abstract={In this letter we propose a robust detection algorithm for audio watermarking for copyright protection. The watermark is embedded in the time domain of an audio signal by the normally used spread spectrum technique. The scheme of detection is an improvement of the conventional correlation detector. A high-pass filter is applied along with the linear prediction error filter for whitening the audio signal and an adaptive threshold is chosen for decision comparing. Experimental results show that our detection algorithm outperforms the conventional one not only because it improves the robustness to normal attacks but also because it can provide the robustness to time-invariant pitch-scale modification.},
keywords={},
doi={10.1093/ietfec/e91-a.11.3389},
ISSN={1745-1337},
month={November},}
Copier
TY - JOUR
TI - Robust Detection Algorithm for Spread Spectrum Audio Watermarking
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3389
EP - 3392
AU - Lili LI
AU - Xiangzhong FANG
PY - 2008
DO - 10.1093/ietfec/e91-a.11.3389
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2008
AB - In this letter we propose a robust detection algorithm for audio watermarking for copyright protection. The watermark is embedded in the time domain of an audio signal by the normally used spread spectrum technique. The scheme of detection is an improvement of the conventional correlation detector. A high-pass filter is applied along with the linear prediction error filter for whitening the audio signal and an adaptive threshold is chosen for decision comparing. Experimental results show that our detection algorithm outperforms the conventional one not only because it improves the robustness to normal attacks but also because it can provide the robustness to time-invariant pitch-scale modification.
ER -