• 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 ...
  • Analysis of multicomponent LFM signals by Teager-Huang-Hough Transform 
    Article dans une revue avec comité de lecture
    BOUCHIKHI, Abdelkhalek; ccBOUDRAA, Abdel-Ouahab; CEXUS, Jean-Christophe; CHONAVEL, Thierry (Institute of Electrical and Electronics Engineers, 2014)
    A novel detection approach of linear FM (LFM) signals, with single or multiple components, in the time-frequency plane of Teager-Huang (TH) transform is presented. The detection scheme that combines TH transform and Hough ...
  • Psi_B-energy operator and cross-power spectral density 
    Article dans une revue avec comité de lecture
    ccBOUDRAA, Abdel-Ouahab; CHONAVEL, Thierry; CEXUS, Jean-Christophe (Elsevier, 2014)
    In this paper we consider the hermitian extension of the cross-Psi_B-energy operator that we will denote by Psi_H. In addition, cross energy terms are formalized through multivariate signals representation. We investigate ...

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