• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Institut de Recherche de l’École navale (IRENAV)
  • View Item
  • Home
  • Institut de Recherche de l’École navale (IRENAV)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Audio watermarking via EMD

Tatouage audio par EMD

Article dans une revue avec comité de lecture
Author
KHALDI, Kais
ccBOUDRAA, Abdel-Ouahab
13094 Institut de Recherche de l'Ecole Navale [IRENAV]

URI
http://hdl.handle.net/10985/8985
DOI
10.1109/TASL.2012.2227733
Date
2013
Journal
IEEE Transactions on Audio, Speech and Language Processing

Abstract

In this paper a new adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD) is introduced. The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into intrinsic oscillatory components called Intrinsic Mode Functions (IMFs). The watermark and the synchronization codes are embedded into the extrema of the last IMF, a low frequency mode stable under different attacks and preserving audio perceptual quality of the host signal. The data embedding rate of the proposed algorithm is 46.9–50.3 b/s. Relying on exhaustive simulations, we show the robustness of the hidden watermark for additive noise, MP3 compression, re-quantization, filtering, cropping and resampling. The comparison analysis shows that our method has better performance than watermarking schemes reported recently.

Files in this item

Name:
IRENav_TASLP_Boudraa_2013.pdf
Size:
1023.Kb
Format:
PDF
View/Open

Collections

  • Institut de Recherche de l’École navale (IRENAV)

Related items

Showing items related by title, author, creator and subject.

  • Voiced speech enhancement based on adaptive filtering of selected intrinsic mode functions 
    Article dans une revue avec comité de lecture
    KHALDI, Kais; TURKI, Monia; ccBOUDRAA, Abdel-Ouahab (World Scientific, 2010)
    In this paper a new method for voiced speech enhancement combining the Empirical Mode Decomposition (EMD) and the Adaptive Center Weighted Average (ACWA) filter is introduced. Noisy signal is decomposed adaptively into ...
  • On signals compression by EMD 
    Article dans une revue avec comité de lecture
    KHALDI, Kais; ccBOUDRAA, Abdel-Ouahab (IET, 2012)
    In this letter a new signals coding framework based on the Empirical Mode Decomposition (EMD) is introduced. The EMD breaks down any signal into a reduced number of oscillating components called Intrinsic Modes Decomposition ...
  • Speech enhancement using empirical mode decomposition and the Teager–Kaiser energy operator 
    Article dans une revue avec comité de lecture
    KHALDI, Kais; ccBOUDRAA, Abdel-Ouahab; KOMATY, Ali (Acoustical Society of America, 2014)
    In this paper a speech denoising strategy based on time adaptive thresholding of intrinsic modes functions (IMFs) of the signal, extracted by empirical mode decomposition (EMD), is introduced. The denoised signal is ...
  • Détection d’épilepsie dans les signaux EEG par graphe de visibilité et un noyau de SVM adapté 
    Communication avec acte
    AVERTY, Tristan; DARE-EMZIVAT, Delphine; ccBOUDRAA, Abdel-Ouahab (GRETSI, 2022-09)
    Dans cet article, nous présentons une stratégie de détection d’épilepsie à partir de signaux EEG (issus d’un seul capteur) basée sur l’algorithme de visibilité, qui consiste à transformer une série temporelle en un graphe ...
  • Relationships between Psi_B energy operator and some time-frequency representations 
    Article dans une revue avec comité de lecture
    ccBOUDRAA, Abdel-Ouahab (Institute of Electrical and Electronics Engineers, 2010)
    Psi_B operator is an energy operator that measures the interactions between two complex signals. In this letter, new properties of Psi_B operator are presented. Connections between Psi_B operator and some time-frequency ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales