Skip to main content

Audio Watermarking Based on the Psychoacoustic Model and Modulated Complex Lapped Transform

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4693))

Abstract

The music industry suffers a multi-billion dollar annual revenue loss due to piracy. Audio watermarking technology is an important technique that is gaining widespread use. However, one of the challenges facing watermarkers is the high sensitivity of the Human Auditory System (HAS). In this paper, we present a novel audio spread spectrum watermarking scheme where the watermark is extracted from the original file.By using the psychoacoustic model this technique efficiently takes advantages of masking phenomena in HAS, in order to embed an important amount of watermark data below the masking threshold of the original input signal. The watermarking is performed in the Modified Complex Lapped Transform (MCLT) domain, which presents a good loss-less reconstruction for audio reconstruction. The computer simulation shows a good imperceptibility and a high robustness to a wide range of unintended and intended attacks.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Malvar, H.: A modulated Complex Lapped Transform And Its Applications to Audio Processing IEEE. In: ICASSP, Phoenix (March 1999)

    Google Scholar 

  2. Kirovski, D., Malvar, H.: Spread-Spectrum Watermarking of Audio Signals. IEEE Transactions on signal Processing (Special Issue on Data Hiding, Phoenix) (2002)

    Google Scholar 

  3. Garcia Hernandez, J.J, Miyatake, M.N., Meana, H.P.: Real-Time MCLT Audio Watermarking and Comparison of Several Whitening Methods in Receptor Side. In: Proceeding of the Eighth IEEE International Symposium on Multimedia, IEEE Computer Society Press, Los Alamitos (2006)

    Google Scholar 

  4. Davies, M.E, Daudet, L.: Sparse audio representations using the MCLT. Elsevier, Amsterdam (2005)

    MATH  Google Scholar 

  5. Seok, J., Hong, J., Kim, J.: A Novel Audio Watermarking Algorithm for Copyright Protection of Digital Audio. ETRI Journal 24 (June 2002)

    Google Scholar 

  6. Zezula, R., Misurec, J.: Audio signal Watrmarking in MCLT domain with the Aid of 2D Pattern. IEEE, NJ, New York (2006)

    Google Scholar 

  7. Swanson, M.D., Zhu, B., Tewfik, A.H., Boney, L.: Robust audio watermarking using perceptual masking. Signal processing. Elsevier, Amsterdam (1998)

    MATH  Google Scholar 

  8. Gordy, J.D., Bruton, L.T.: Performance Evaluation of Digital Audio Watermarking Algorithms. Masterthesis, University of Calgary, Canada, pp. 337–355 (2000)

    Google Scholar 

  9. Cvejic, N., Seppanen, T.: Improving Audio Watermarking Scheme Using Psychoacoustic Watermark. Mediateam, Finaland (2004)

    Google Scholar 

  10. Malvar, H.: Signal processing with lapped transforms. Artech house, Norwood, MA (1992)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mirza, H.H., Adli, A., Thai, H.D., Nagata, Y., Nakao, Z. (2007). Audio Watermarking Based on the Psychoacoustic Model and Modulated Complex Lapped Transform. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74827-4_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74827-4_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74826-7

  • Online ISBN: 978-3-540-74827-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics