Name
Title | ||
|---|---|---|
Reducing The Computational Complexity Of The Reference-Sharing Based Self-Embedding Watermarking Approach |
Abstract | ||
|---|---|---|
Reference-sharing based self-embedding watermarking schemes had been shown to be an effective way to avoid the tampering coincidence and the reference waste problems. Typical reference-sharing based schemes adopt pseudo-random binary matrices as the encoding matrices to generate the reference information. This paper investigate to reduce the computational complexity of the reference-sharing based self-embedding watermarking approach by using the sparse binary matrices as the encoding matrices. Experimental results demonstrate the proposed approach can reduce the computational complexity significantly while maintaining the same tampering restoration capability as the traditional. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00021-9_56 | CLOUD COMPUTING AND SECURITY, PT VI |
Keywords | Field | DocType |
Self-embedding watermarking, Computational complexity, Tamper detection and recovery, Sparse matrices | Digital watermarking,Matrix (mathematics),Computer science,Theoretical computer science,Coincidence,Self-embedding,Sparse matrix,Binary number,Encoding (memory),Computational complexity theory,Distributed computing | Conference |
Volume | ISSN | Citations |
11068 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongmei Niu | 1 | 2 | 6.44 |
| Hongxia Wang | 2 | 197 | 16.93 |
| M. Cheng | 3 | 154 | 20.36 |