Name
Abstract | ||
|---|---|---|
RST invarian watermarking scheme is proposed in this paper based on the SIFT feature points and improved pseudo-Zernike moment. Firstly, feature points are detected using SIFT, and some suitable points are selected to form localized feature regions which are scaled to a standard sized. After computing these regions by the improved pseudo-Zernike moments of these regions , the digital watermark are embedded into the host image by quantizing some low-lever moments. Experimental results show this scheme is robust against the rotation, shearing, JPEG compression, noise and filtering attack. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISCID.2009.151 | ISCID (2) |
Keywords | Field | DocType |
sift,psnr,scale invariant feature transform,data mining,feature extraction,digital watermark,robustness,method of moments,watermarking | Scale-invariant feature transform,Computer vision,Digital watermarking,Pattern recognition,Computer science,Filter (signal processing),Feature extraction,Robustness (computer science),Zernike polynomials,Artificial intelligence,Quantization (signal processing),Method of moments (statistics) | Conference |
Volume | Issue | Citations |
2 | null | 1 |
PageRank | References | Authors |
0.37 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinguang Sun | 1 | 13 | 2.30 |
| Wei He | 2 | 1 | 0.71 |