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Proceedings Paper

Optimal 3D object surface identification
Author(s): Mehmet Celenk
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Paper Abstract

This paper describes a method of optimal 3D object surface identification. First, the spatial and frequency domain approaches are presented for the determination of an optimal grid spacing for 3D object surface representation. The spatial domain approach is based on the measurement of the total variations of the object surface function f(x,y) in the constant x and constant y planes and the frequency domain approach utilizes the Nyquist criterion and an ideal 2D rectangular low-pass filter in an iterative operation. Two error criteria are defined based on the magnitude and shape features of f(x,y) as the measure of effectiveness of the optimal grid spacing for 3D object surface representation. Second, a feature-based object surface identification method is described based on the boundary features of the object and model surface cross sections.

Paper Details

Date Published: 6 August 1993
PDF: 12 pages
Proc. SPIE 2056, Intelligent Robots and Computer Vision XII: Active Vision and 3D Methods, (6 August 1993); doi: 10.1117/12.150192
Show Author Affiliations
Mehmet Celenk, Ohio Univ. (United States)


Published in SPIE Proceedings Vol. 2056:
Intelligent Robots and Computer Vision XII: Active Vision and 3D Methods
David P. Casasent, Editor(s)

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