Name
Abstract | ||
|---|---|---|
The problem of optimum watermark recovery in a non additive, non Gaussian framework is addressed. Watermark casting is carried
out on the frequency domain according to an additive-multiplicative rule. The structure of the optimum decoder is derived
based on statistical decision theory. The Neyman-Pearson criterion is used to minimize the probability of missing the watermark
for a given false detection rate. Experimental results highlights the superiority of the novel detector scheme with respect
to conventional correlation-based decoding.
|
Year | DOI | Venue |
|---|---|---|
1999 | 10.1007/10719724_12 | Information Hiding |
Keywords | Field | DocType |
non-additive full frame dft,optimum decoding,frequency domain | Computer science,Watermark,Artificial intelligence,Jpeg compression,Detector,Frequency domain,Computer vision,False detection,Statistical decision theory,Algorithm,Speech recognition,Gaussian,Decoding methods | Conference |
Volume | ISSN | ISBN |
1768 | 0302-9743 | 3-540-67182-X |
Citations | PageRank | References |
13 | 1.69 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessia De Rosa | 1 | 312 | 20.66 |
| M. Barni | 2 | 3091 | 246.21 |
| franco bartolini | 3 | 539 | 57.39 |
| Vito Cappellini | 4 | 521 | 64.85 |
| Alessandro Piva | 5 | 2231 | 157.21 |