Abstract
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.