Name
Abstract | ||
|---|---|---|
Bit extraction is an essential component of an image hashing system. A good bit extraction scheme should preserve the performance achieved at the feature representation level. In other words the robustness discrimination tradeoff measured by ROC analysis should be preserved. This is dependent on several factors such as, the encountered noise and the number of bits that can be extracted per sample. This paper investi- gates the relationship between these parameters and proposes some theoretical bounds in achieving a good tradeoff. The analysis primarily focuses on the bit extraction method pro- posed in (1) and its performance is compared with a scalar quantization based hashing method. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICIP.2008.4711993 | ICIP |
Keywords | Field | DocType |
cryptography,feature extraction,image coding,image representation,ROC analysis,bit extraction method,cryptography,feature representation level,locality preserving image hash,scalar quantization based hashing method,Locality preserving hashing,correspondence preserving hash,hash modeling,quantization based hashing | Locality,Pattern recognition,Locality preserving hashing,Computer science,Cryptography,Feature extraction,Robustness (computer science),Artificial intelligence,Hash function,K-independent hashing,2-choice hashing | Conference |
ISSN | Citations | PageRank |
1522-4880 | 0 | 0.34 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sujoy Roy | 1 | 169 | 17.35 |
| Qibin Sun | 2 | 661 | 55.19 |
| Ton Kalker | 3 | 1203 | 140.78 |