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Proceedings Paper

Low-cost real-time automatic wheel classification system
Author(s): Behrouz N. Shabestari; John W. V. Miller; Victoria Wedding
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Paper Abstract

This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

Paper Details

Date Published: 1 November 1992
PDF: 5 pages
Proc. SPIE 1823, Machine Vision Applications, Architectures, and Systems Integration, (1 November 1992); doi: 10.1117/12.132077
Show Author Affiliations
Behrouz N. Shabestari, Edison Industrial Systems Ctr. (United States)
John W. V. Miller, Edison Industrial Systems Ctr. (United States)
Victoria Wedding, Edison Industrial Systems Ctr. (United States)


Published in SPIE Proceedings Vol. 1823:
Machine Vision Applications, Architectures, and Systems Integration
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

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