Name
Abstract | ||
|---|---|---|
In this paper, a fast color feature is presented for real-time image retrieval. The feature is based on Dense SIFT (DSIFT) in the multi-scale RGB space. A new sum function is proposed to accelerate feature extraction instead of Gaussian weighting function. In addition, a novel randomized segment-based sampling algorithm is introduced to filter out superfluous features. In the image retrieval stage, a similarity metric is provided to measure the match between the query and reference images. After the experiments are conducted, RGB-DSIFT is more resistant to common image deformations than the original DSIFT, and more efficient than SIFT, CSIFT, GLOH feature in the processing time. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICNIDC.2012.6418794 | PROCEEDINGS OF THE 3RD IEEE INTERNATIONAL CONFERENCE ON NETWORK INFRASTRUCTURE AND DIGITAL CONTENT (IEEE IC-NIDC 2012) |
Keywords | Field | DocType |
RGB-DSIFT, Multi-scale, Color, Filter, Magnitude, Similarity measure | Computer vision,GLOH,Color histogram,Pattern recognition,Feature detection (computer vision),Feature (computer vision),Feature extraction,Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Mathematics,Visual Word,Color image | Conference |
Citations | PageRank | References |
1 | 0.35 | 6 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chong Huang | 1 | 8 | 3.17 |
| Yuan Dong | 2 | 774 | 151.17 |
| Shusheng Cen | 3 | 6 | 2.45 |
| Hongliang Bai | 4 | 152 | 18.48 |
| Wei Liu | 5 | 8 | 1.88 |
| Jiwei Zhang | 6 | 15 | 3.77 |
| jian zhao | 7 | 1 | 0.35 |