Abstract
Three dimension object recognition is a basic problem of computer vision field. There were uncertainness, uncompleteness and unclarity in acquirement data as invariant moment theory was applied to recognize three dimension image target, therefore recognition efficiency could not meet the needs of actual system. By combining Dempster-Shafer evidence reasoning with invariant moment theory, intelligence image fusion recognition algorithm was present. A basic belief assignment function was constructed, and a classify rule was built. Dempster combination rule and the absorptive method ware used for recognizing three dimension airplane image. The result of simulation indicates that absorptive method have higher recognition efficiency than Dempster combination rule.
| Original language | English |
|---|---|
| Pages | 4132-4136 |
| Number of pages | 5 |
| State | Published - 2004 |
| Event | WCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings - Hangzhou, China Duration: 15 Jun 2004 → 19 Jun 2004 |
Conference
| Conference | WCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings |
|---|---|
| Country/Territory | China |
| City | Hangzhou |
| Period | 15/06/04 → 19/06/04 |
Keywords
- Dempster-Shafer evidence reasoning
- Intelligence image fusion recognition algorithm
- Invariant moment
- Three dimension airplane image recognition