Name
Title | ||
|---|---|---|
A fast image retrieval using the unification search method of binary classification and dimensionality condensation of feature vectors |
Abstract | ||
|---|---|---|
We present the two-stage content-based image retrieval as a new fast image retrieval approach using the unification search method of binary classification and dimensionality condensation of feature vectors. The method successfully reduces the overall retrieval time, while maintaining the same retrieval relevance as the conventional exhaustive search method. By the extensive computer simulations, we have observed that the method is more effective as user-specific threshold for the similarity score increase. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11553939_35 | KES (3) |
Keywords | Field | DocType |
unification search method,conventional exhaustive search method,overall retrieval time,dimensionality condensation,extensive computer simulation,new fast image retrieval,binary classification,feature vector,two-stage content-based image retrieval,retrieval relevance,computer simulation,exhaustive search | Data mining,Search algorithm,Binary classification,Computer science,Image retrieval,Artificial intelligence,Distributed computing,Similitude,Feature vector,Pattern recognition,Brute-force search,Unification,Curse of dimensionality | Conference |
Volume | ISSN | ISBN |
3683 | 0302-9743 | 3-540-28896-1 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jungwon Cho | 1 | 46 | 11.21 |
| Seungdo Jeong | 2 | 25 | 8.82 |
| Byung-Uk Choi | 3 | 50 | 14.62 |