Paper
13 April 2018 A low-cost machine vision system for the recognition and sorting of small parts
Gustavo Barea, Brian W. Surgenor, Vedang Chauhan, Keyur D. Joshi
Author Affiliations +
Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106961O (2018) https://doi.org/10.1117/12.2309957
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria
Abstract
An automated machine vision-based system for the recognition and sorting of small parts was designed, assembled and tested. The system was developed to address a need to expose engineering students to the issues of machine vision and assembly automation technology, with readily available and relatively low-cost hardware and software. This paper outlines the design of the system and presents experimental performance results. Three different styles of plastic gears, together with three different styles of defective gears, were used to test the system. A pattern matching tool was used for part classification. Nine experiments were conducted to demonstrate the effects of changing various hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. It was found that the system could achieve a maximum system accuracy of 95% at a feed rate of 60 parts/min, for a given set of parameter settings. Future work will be looking at the effect of lighting.
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Gustavo Barea, Brian W. Surgenor, Vedang Chauhan, and Keyur D. Joshi "A low-cost machine vision system for the recognition and sorting of small parts", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961O (13 April 2018); https://doi.org/10.1117/12.2309957
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KEYWORDS
Machine vision

Inspection

Image classification

Cameras

Light sources and illumination

Servomechanisms

Image processing

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