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Proceedings Paper

Knowledge-based object recognition technique for robotics assembly application
Author(s): H. Najjari; Simon J. Steiner
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Paper Abstract

This paper presents a flexible object recognition system which has been developed using a knowledge based approach for robotics assembly applications. The developed system overcomes some limitations of conventional object recognition techniques. The system can robustly recognize any number of objects of any shape, where the objects could be with any random position and orientation, and lying on any side or face. The system is flexible such that it can accommodate any number of new objects of any shape without the need to reprogram the system. The recognition method is based on a knowledge based approach, and the record of the boundary pixels is used for the extraction of a number of potential recognition features in order to recognize the objects. Depending on the shape and size of the objects introduced to the system, in its Training Mode, the system automatically selects a minimum number of important recognition features for robustly recognizing all the objects, and it automatically modifies the recognition program and feature extraction program in its Operation Mode based on the selected features.

Paper Details

Date Published: 3 October 1995
PDF: 9 pages
Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222713
Show Author Affiliations
H. Najjari, Univ. of Birmingham (United Kingdom)
Simon J. Steiner, Univ. of Birmingham (United Kingdom)


Published in SPIE Proceedings Vol. 2588:
Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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