DocumentCode
2964701
Title
Periodic signaling scheme in oblivious data hiding
Author
Gang, Litao ; Akansu, Ali N. ; Ramkumar, M.
Author_Institution
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
Volume
2
fYear
2000
fDate
Oct. 29 2000-Nov. 1 2000
Firstpage
1851
Abstract
In the oblivious watermarking, information is extracted without reference to the original host signal, whose energy is much larger than that of the watermark signal. Suppressing host noise is a great concern. Some non-linear embedding methods, e.g. quantization index modulation (QIM) can greatly suppress the host noise. In this method, the signaling is periodic. We analyze the maximum likelihood (ML) detector for the QIM signaling scheme, and compare the error probability with a hard decision detector. Based on it, a new periodic signaling scheme is proposed and its optimum and suboptimal detection is derived. Through analysis and simulation, we demonstrate its advantage in term of PE-SNR over the existing methods.
Keywords
copy protection; data encapsulation; error statistics; maximum likelihood detection; modulation; noise; optimisation; quantisation (signal); security of data; telecommunication security; telecommunication signalling; PE-SNR; error probability; hard decision detector; host noise suppression; host signal energy; information extraction; maximum likelihood detector; multimedia copyright authentication; multimedia copyright protection; nonlinear embedding methods; oblivious data hiding; oblivious watermarking; optimal detection; periodic signaling; quantization index modulation; simulation; steganography; suboptimal detection; watermark signal; Analytical models; Data encapsulation; Data engineering; Detectors; Maximum likelihood detection; Quantization; Robustness; Signal analysis; Steganography; Watermarking;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
Conference_Location
Pacific Grove, CA, USA
ISSN
1058-6393
Print_ISBN
0-7803-6514-3
Type
conf
DOI
10.1109/ACSSC.2000.911308
Filename
911308
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