Extraction of features from 3D laser scanner cloud data

Vincent H. Chan; Colin H. Bradley; Geoffrey W. Vickers

doi:10.1117/12.294457

10 December 1997 Extraction of features from 3D laser scanner cloud data

Vincent H. Chan, Colin H. Bradley, Geoffrey W. Vickers

Proceedings Volume 3204, Three-Dimensional Imaging and Laser-based Systems for Metrology and Inspection III; (1997) https://doi.org/10.1117/12.294457
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States

Abstract

One of the road blocks on the path of automated reverse engineering has been the extraction of useful data from the copious range data generated from 3-D laser scanning systems. A method to extract the relevant features of a scanned object is presented. A 3-D laser scanner is automatically directed to obtain discrete laser cloud data on each separate patch that constitutes the object's surface. With each set of cloud data treated as a separate entity, primitives are fitted to the data resulting in a geometric and topologic database. Using a feed-forewarn neural network, the data is analyzed for geometric combinations that make up machine features such as through holes and slots. These features are required for the reconstruction of the solid model by a machinist or feature based CAM algorithms, thus completing the reverse engineering cycle.

Citation Download Citation

Vincent H. Chan, Colin H. Bradley, and Geoffrey W. Vickers "Extraction of features from 3D laser scanner cloud data", Proc. SPIE 3204, Three-Dimensional Imaging and Laser-based Systems for Metrology and Inspection III, (10 December 1997); https://doi.org/10.1117/12.294457

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