Name
Abstract | ||
|---|---|---|
Recently, web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hashing techniques are used for the image registration, management and retrieval as the identifier also, investigations have been performed to raise the hash performance like discernment. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which is based on histogram bin population method. So far, many studies have proven that image hashing techniques based on this histogram are robust against image processing and geometrical attacks. We modified existing image hashing method developed by our research team []. The main idea of the paper is that it helps generate more fluent hash string if we have specific length of histogram bin. Another operation is empowering weighting factor into hash string at each level. Thus, we can raise the magnitude of hash string generated from same context or features and also strengthen the robustness of generated hash. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s11042-010-0724-7 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Image hash,Hierarchical hash generation,Robustness,Statistical hypothesis testing | Computer vision,Pattern recognition,Double hashing,Computer science,Universal hashing,Rolling hash,Feature hashing,Artificial intelligence,Hash function,Dynamic perfect hashing,Hash table,Linear hashing | Journal |
Volume | Issue | ISSN |
61 | 1 | 1380-7501 |
Citations | PageRank | References |
16 | 0.70 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Soo Choi | 1 | 29 | 3.62 |
| Jong Hyuk Park | 2 | 1661 | 193.82 |