Name
Abstract | ||
|---|---|---|
In this paper, we present a watermarking scheme based on the DWT (Discrete Wavelet Transform) and the ANN (Artificial Neural Network) to ensure the copyright protection of the digital images. To embed the watermark, the interested regions where the watermark is embed must be decided by the SOFM (Self-Organizing Feature Maps). Among the classified nodes, we select the middle of nodes and establish the average of node as threshold. The established threshold applies the only wavelet coefficients of the selected node, so we can reduce the time cost. Using the SOFM that much safer than other algorithms because unauthorized user can't know the result of training by the SOFM. So even the watermark casting process is in public, the attackers or unauthorized users still cannot remove the watermark from the watermarked image. As the result, the fidelity of the image is excellent than any other algorithm, and the process is good at the strength test-filtering, geometric transform and etc. Furthermore, it is also robust in JPEG compression as well. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-36901-5_28 | APWeb |
Keywords | Field | DocType |
watermark casting process,watermarked image,unauthorized user,established threshold,jpeg compression,digital image,semi-blind watermarking,classified node,discrete wavelet transform,selected node,artificial neural network,self-organizing coefficient,self organization | Steganography,Computer vision,Digital watermarking,Computer science,Image processing,Digital image,Watermark,Discrete wavelet transform,Artificial intelligence,Artificial neural network,Wavelet | Conference |
Volume | ISSN | ISBN |
2642 | 0302-9743 | 3-540-02354-2 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sung-Kwan Je | 1 | 6 | 4.30 |
| Chang-jin Seo | 2 | 0 | 0.34 |
| Jin-young Lee | 3 | 0 | 0.34 |
| Eui-Young Cha | 4 | 49 | 11.24 |