Abstract
In allusion to the deficiencies of object recognition based on corners, a method for extracting corner feature from images was proposed. This feature is invariant to translation, rotation, scale change and is shownrobust to addition of noise. The pattern vectors were obtained using global and local constraint conditions and the dimension of vectors in the method according to the spatial relationships between corners. To solve the problems caused by the attitude changes of the objects, the 3D modes were used to construct the 2D views. We presented a system to recognize the objects with changes in 3D viewpoint using this feature and BP network. The performance on the obtained experimental results demonstrates that the proposed method is more effective than the other three ones.
| Original language | English |
|---|---|
| Pages (from-to) | 84-87 |
| Number of pages | 4 |
| Journal | Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) |
| Volume | 38 |
| Issue number | 6 |
| Publication status | Published - Jun 2010 |
Keywords
- Backpropagation network
- Corner points
- Feature extraction
- Image processing
- Object recognition