Name
Abstract | ||
|---|---|---|
In scale-space feature based watermarking schemes, the watermark is usually embedded in spatial domain so that watermark robustness is not satisfactory. In this paper, a novel image watermarking scheme is presented by combining scale-space feature based watermark synchronization and nonsubsampled Contourlet transform (NSCT) based watermark embedding. Watermark synchronization is achieved based on the local circular regions, which can be generated using the scale-invariant feature transform (SIFT). In the encoder, the watermark is embedded into the NSCT coefficients in a content-based and rotation-invariant manner by odd-even quantization. In the decoder, the watermark can be extracted directly from the local regions using the proposed coefficient property detector (CPD). Simulation results and comparisons show that the proposed scheme can efficiently resist signal processing attacks, geometric attacks as well as some combined attacks. |
Year | Venue | Field |
|---|---|---|
2008 | DIGITAL WATERMARKING | Signal processing,Scale-invariant feature transform,Digital watermarking,Computer science,Scale space,Theoretical computer science,Watermark,Artificial intelligence,Contourlet,Computer vision,Pattern recognition,Encoder,Quantization (signal processing) |
DocType | Volume | ISSN |
Conference | 5450 | 0302-9743 |
ISBN | Citations | PageRank |
978-3-642-04437-3 | 4 | 0.42 |
References | Authors | |
23 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Leida | 1 | 684 | 60.56 |
| Guo Baolong | 2 | 12 | 3.69 |
| Pan Jeng-Shyang | 3 | 2466 | 269.74 |
| Yang Liu | 4 | 8 | 1.50 |