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Proceedings Paper

Classification of Range Surface Type Using Optically Generated Derivative Estimates
Author(s): Suzanne A. Liebowitz; David P. Casasent
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Paper Abstract

We describe a technique to classify surface types from range data using local derivative estimates. We propose an optical architecture using acousto-optic devices to efficiently compute these derivatives. The derivative estimates are combined into curvature functions which are scale-, translation-, and rotation-invariant, and the surface types are determined from these curvature features. Results are presented for the classification of test range surfaces.

Paper Details

Date Published: 1 March 1990
PDF: 21 pages
Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); doi: 10.1117/12.969738
Show Author Affiliations
Suzanne A. Liebowitz, Carnegie Mellon University (United States)
David P. Casasent, Carnegie Mellon University (United States)


Published in SPIE Proceedings Vol. 1192:
Intelligent Robots and Computer Vision VIII: Algorithms and Techniques
David P. Casasent, Editor(s)

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