- Title
- Feature recognition in 3D surface models using self-organizing maps
- Creator
- Buhr, Richard Otto
- Subject
- Self-organizing maps, Neural networks (Computer science), Computer vision
- Date
- 2008-11-18T09:06:20Z
- Type
- Thesis
- Identifier
- uj:14724
- Identifier
- http://hdl.handle.net/10210/1729
- Description
- M.Ing., This project investigates the use of Self-Organizing Maps (SOM) for feature recognition and analysis in 3D objects. Object data was generated to simulate data obtained from 3D scanning and trained using SOM. The trained data was analysed using speci cally developed software. The feature recognition and analysis process can be summarized as follows: a 3D object le is converted to a pure 3D data le, this data le is trained using the SOM algorithm after which the output is analyzed using a 3D object viewer and SOM data display.
- Contributor
- Prof. Z. Katz Dr. J.J. Naude
- Full Text
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