Dalgacik uzayinda öǧrenmeye dayali sayisal ses damgalama

Translated title of the contribution: Digital audio watermarking by learning in wavelet domain

Serap Kirbiz*, Bilge Günsel

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Most of the watermark (WM) decoding schemes use correlation-based methods because of their simplicity. Generally, a decision threshold specified semi-automatically is used at the decoding site. The main problem of the correlation-based decoders is the existence of undesirable correlation between the embedded signal and the host signal that makes the decision threshold specification harder, especially in noisy channels. In this paper, WM decoding is modeled as a pattern recognition problem, thus eliminates the threshold specification problem by learning the embedded data in wavelet domain followed by a nonlinear classification. Furthermore, the encoding performance is improved by perceptual control of Watermark-to-Signal-Ratio (WSR) without disturbing imperceptibility. When the WSR is higher than -30 dB, the decoding and detection performances of the developed system are greater than 99% and 98%, respectively. System false alarm ratios remain less than 2%.

Translated title of the contributionDigital audio watermarking by learning in wavelet domain
Original languageTurkish
Title of host publication2006 IEEE 14th Signal Processing and Communications Applications Conference
DOIs
Publication statusPublished - 2006
Event2006 IEEE 14th Signal Processing and Communications Applications - Antalya, Turkey
Duration: 17 Apr 200619 Apr 2006

Publication series

Name2006 IEEE 14th Signal Processing and Communications Applications Conference
Volume2006

Conference

Conference2006 IEEE 14th Signal Processing and Communications Applications
Country/TerritoryTurkey
CityAntalya
Period17/04/0619/04/06

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