Name
Abstract | ||
|---|---|---|
In this paper, we present a novel descriptor called uniform rotation invariant gradient(URIG) aiming at texture classification under variant rotation and illumination condition. Instead of using URIG directly, a 2D descriptor can be formulated combining URIG with average of local pixels. Given a texture image, such 2D descriptors are extracted from every pixel followed by clustering. The centers of clustering can be viewed as a texton dictionary over which a histogram is computed as the representation of given texture image Experiments are carried out on Outex and CUReT databases comparing to state-of-the-art approaches. Our proposed method achieved promising performance against illumination and rotation changes with least cost for representing histogram dimension. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICIP.2015.7351485 | ICIP |
Keywords | Field | DocType |
texture classification,rotation and illumination invariant,local descriptor | Computer vision,Pattern recognition,Computer science,Image texture,Invariant (mathematics),Artificial intelligence | Conference |
Volume | ISSN | Citations |
2015-December | 1522-4880 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhao Wenteng | 1 | 2 | 0.70 |
| Lu ZQ | 2 | 47 | 9.45 |
| QM | 3 | 464 | 72.05 |