Name
Abstract | ||
|---|---|---|
For the classical watermark embedment model I = 1 + /spl alpha/W, the corresponding watermark detection has its limitation in its need of a fixed parameter for extracting watermarks. If the extraction parameter is too large, we cannot extract the watermark from the image that contains watermarks; if it is too small, the extracted watermarks may be blurred. This paper proposes a novel watermark extraction method. First, we treat the watermark information as noise for the watermarked image in its spatial domain. We then magnify the noise before detection. Next, we recover the watermark information by adjusting the extracted data from the frequency domain according to our global minimum method. Experimental results show that our watermark extraction method is more valid and accurate than the classical method. It can greatly reduce extraction errors. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICIG.2004.146 | ICIG |
Keywords | Field | DocType |
classical method,image coding,noise,classical watermark embedment model,global minimum method,magnifying noise,watermark detection,extraction error,watermark extraction method,feature extraction,extraction parameter,fixed parameter,watermark extraction,watermarking,spatial domain,corresponding watermark detection,watermarked image,watermark information,global minimum decoder,novel watermark extraction method,decoding,frequency domain | Frequency domain,Computer vision,Digital watermarking,Pattern recognition,Computer science,Approximation theory,Image quality,Watermark,Feature extraction,Fast Fourier transform,Artificial intelligence,Decoding methods | Conference |
ISBN | Citations | PageRank |
0-7695-2244-0 | 3 | 0.40 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhigeng Pan | 1 | 1312 | 146.88 |
| Li Li | 2 | 237 | 34.83 |
| Mingmin Zhang | 3 | 256 | 40.55 |
| David Zhang | 4 | 2337 | 102.40 |