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Proceedings Paper

Rule-Based For A String Code Pattern Recognition Processor
Author(s): David Casasent; Sung-IL Chien
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Paper Abstract

A 3-D distortion-invariant multi-class object identification problem is addressed. Our new, fast and robust string-code generation technique (using optical and digital methods) makes the rule-based system quite practical and attractive. Emphasis is given to our rule-based system and to initial data results. Excellent multi-class recognition and reasonable object distortions can be accommodated in this system. We achieved 80-90% correct recognition (PC) for 10 object classes and ±30° 3-D distortions and full 360° in-plane distortions.

Paper Details

Date Published: 27 March 1989
PDF: 13 pages
Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); doi: 10.1117/12.960254
Show Author Affiliations
David Casasent, Carnegie Mellon University (United States)
Sung-IL Chien, Carnegie Mellon University (United States)

Published in SPIE Proceedings Vol. 1002:
Intelligent Robots and Computer Vision VII
David P. Casasent, Editor(s)

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