Name
Abstract | ||
|---|---|---|
HU moments aren't invariant for scaling in the discrete state, so they are improved in the paper. The improved moments are consistent with region, boundary and discrete situation. Therefore, they are applied to three-dimensional object recognition. Firstly the improved moments are calculated. Then the similarity measure is computed between objects to be recognized and the standard one. Finally experiments are simulated by MATLAB, and experimental results demonstrate that the improved moments are invariant to the translation, rotating and scaling of objects, the recognition rate is relatively high and the proposed algorithm has some practical value. So the feasibility of the proposed method is proved in the paper. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICAL.2012.6308139 | 2012 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS (ICAL) |
Keywords | Field | DocType |
object recognition, HU moments, improve, similarity measure | MATLAB,3D single-object recognition,Pattern recognition,Similarity measure,Control theory,Algorithm,Artificial intelligence,Invariant (mathematics),Velocity Moments,Scaling,Mathematics,Cognitive neuroscience of visual object recognition | Conference |
Volume | Issue | ISSN |
null | null | 2161-8151 |
Citations | PageRank | References |
1 | 0.35 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Zhang | 1 | 1 | 0.69 |
| Fei Xiang | 2 | 1 | 1.03 |
| Jiexin Pu | 3 | 92 | 19.85 |
| Zhiyong Zhang | 4 | 164 | 18.42 |