Name
Abstract | ||
|---|---|---|
This paper proposes a Content-Based Image Retrieval (CBIR) system applicable in mobile devices. Due to the fact that different queries to a content-based image retrieval (CBIR) system emphasize different subsets of a large collection of features, most CBIR systems using only a few features are therefore only suitable for retrieving certain types of images. In this research we combine a wide range of features, including edge information, texture energy, and the HSV color distributions, forming a feature space of up to 1053 dimensions, in which the system can search for features most desired by the user. Through a training process using the AdaBoost algorithm(9) our system can efficiently search for important features in a large set of features, as indicated by the user, and effectively retrieve the images according to these features. The characteristics of the system meet the requirements of mobile devices for performing image retrieval. The experimental results show that the performance of the proposed system is sufficiently applicable for mobile devices to retrieve images from a huge database. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1142/S021800140600482X | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
mobile-dependent application, content-based image retrieval (CBIR), orientation-distance, local edge pattem (LEP), wavelet energy, HSV color space, AdaBoost | HSL and HSV,Computer vision,Feature vector,AdaBoost,Pattern recognition,Computer science,Image retrieval,Mobile device,Artificial intelligence,Content-based image retrieval,Visual Word | Journal |
Volume | Issue | ISSN |
20 | 4 | 0218-0014 |
Citations | PageRank | References |
10 | 0.50 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hwei-jen Lin | 1 | 59 | 8.91 |
| Yang-Ta Kao | 2 | 37 | 4.47 |
| Fuwen Yang | 3 | 1051 | 74.00 |
| patrick s p wang | 4 | 303 | 47.66 |