Name
Abstract | ||
|---|---|---|
This paper describes a method for recognizing partially occluded objects to realize a bin-picking task under different levels of illumination brightness by using the eigenspace analysis. In the proposed method, a measured color in the RGB color space is transformed into the HSV color space. Then, the hue of the measured color, which is invariant to change in illumination brightness and direction, is used for recognizing multiple objects under different levels of illumination conditions. The proposed method was applied to real images of multiple objects under different illumination conditions, and the objects were recognized and localized successfully |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/IROS.1997.655139 | Intelligent Robots and Systems, 1997. IROS '97., Proceedings of the 1997 IEEE/RSJ International Conference |
Keywords | Field | DocType |
brightness,eigenvalues and eigenfunctions,image colour analysis,learning systems,lighting,manipulators,object recognition,robot vision,HSV color space,RGB color space,bin-picking task,brightness,eigenspace,illumination invariance,manipulator,object recognition,object verification,partially occluded objects,robot vision,visual learning | Computer vision,HSL and HSV,Color constancy,Color space,Computer science,RGB color space,Hue,Color model,Artificial intelligence,Real image,Brightness | Conference |
Volume | ISBN | Citations |
2 | 0-7803-4119-8 | 1 |
PageRank | References | Authors |
0.38 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| kohtaro ohba | 1 | 317 | 66.11 |
| Yoichi Sato | 2 | 2289 | 167.78 |
| Katsushi Ikeuchi | 3 | 4651 | 881.49 |