Range image segmentation using local approximation of scan lines with application to CAD model acquisition

Authors:
Inas Khalifa;Medhat Moussa;Mohamed Kamel
Affiliations:
Systems Design Engineering Dept., University of Waterloo, Waterloo, ON N2L 3G1, Canada;School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada;Systems Design Engineering Dept., University of Waterloo, Waterloo, ON N2L 3G1, Canada
Venue:
Machine Vision and Applications
Year:
2003

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Abstract

Automatic acquisition of CAD models from existing objects requires accurate extraction of geometric and topological information from the input data. This paper presents a range image segmentation method based on local approximation of scan lines. The method employs edge models that are capable of detecting noise pixels as well as position and orientation discontinuities of varying strengths. Region-based techniques are then used to achieve a complete segmentation. Finally, a geometric representation of the scene, in the form of a surface CAD model, is produced. Experimental results on a large number of real range images acquired by different range sensors demonstrate the efficiency and robustness of the method.