Name
Title | ||
|---|---|---|
Global matching to enhance the strength of local intensity order pattern feature descriptor |
Abstract | ||
|---|---|---|
Local intensity order pattern feature descriptor is proposed to extract the feature of image recently. However, it did not provide the global information of an image. In this paper, a simple, efficient and robust feature descriptor is presented, which is realized by adding the global information to local intensity features. A descriptor, which utilizes local intensity order pattern and/or global matching, is proposed to gather the global information with local intensity order. Experimental results shows that the proposed hybrid approach outperform over the state-of-the art feature extraction method like scale-invariant feature transform, local intensity order pattern and DAISY for standard oxford dataset. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-39065-4_60 | ISNN (1) |
Keywords | Field | DocType |
global information,proposed hybrid approach,local intensity order pattern,local intensity feature,scale-invariant feature,feature descriptor,robust feature descriptor,state-of-the art feature extraction,local intensity order,global matching,image classification,feature extraction | Computer science,Global information,Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Feature transform,Contextual image classification,Computer vision,Global matching,Feature descriptor,Pattern recognition,Feature (computer vision),Feature extraction,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.36 | 27 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hassan Dawood | 1 | 67 | 14.45 |
| Hussain Dawood | 2 | 53 | 12.90 |
| Ping Guo | 3 | 601 | 85.05 |