Flexible gray-level vision system based on multiple cell-feature description and generalized Hough transform

Mutsuo Sano; Akira Ishii; Shin-Ichi Meguro

doi:10.1117/12.25140

1 February 1991 Flexible gray-level vision system based on multiple cell-feature description and generalized Hough transform

Mutsuo Sano, Akira Ishii, Shin-Ichi Meguro

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Proceedings Volume 1381, Intelligent Robots and Computer Vision IX: Algorithms and Techniques; (1991) https://doi.org/10.1117/12.25140
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

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.

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Mutsuo Sano, Akira Ishii, and Shin-Ichi Meguro "Flexible gray-level vision system based on multiple cell-feature description and generalized Hough transform", Proc. SPIE 1381, Intelligent Robots and Computer Vision IX: Algorithms and Techniques, (1 February 1991); https://doi.org/10.1117/12.25140

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