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Proceedings Paper

Flexible gray-level vision system based on multiple cell-feature description and generalized Hough transform
Author(s): Mutsuo Sano; Akira Ishii; Shin-Ichi Meguro
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Paper Abstract

This paper presents a flexible and highly-reliable gray-level vision system based on multiple cell-feature descriptions using only three basic operation modules: extended convolution radially traversing probing and histogram compression. The generalized Hough transform is introduced as a universal method for object model matching. Model learning is automatically performed by acquiring image samples while rotating each object. A prototype system demonstrates successful recognition of mechanical parts.

Paper Details

Date Published: 1 February 1991
PDF: 10 pages
Proc. SPIE 1381, Intelligent Robots and Computer Vision IX: Algorithms and Techniques, (1 February 1991); doi: 10.1117/12.25140
Show Author Affiliations
Mutsuo Sano, NTT Human Interface Labs. (Japan)
Akira Ishii, NTT Affiliated Companies Headquarters (Japan)
Shin-Ichi Meguro, NTT Integrated Communications Systems Sector (Japan)


Published in SPIE Proceedings Vol. 1381:
Intelligent Robots and Computer Vision IX: Algorithms and Techniques
David P. Casasent, Editor(s)

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