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A systematic methodology for determining/optimizing a machine vision system's capability

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Abstract

This paper presents a systematic methodology based on Taguchi methods to determine and optimize a machine vision system's capability. Seven factors were studied in anL 27(313) orthogonal array: lens type, color of the background, distance between two objects on the target, distance between the camera and the target, filter, lighting source, and angle between the optic axis of the camera and the surface of the target. The optimal factor-level combination was determined from the experiment results, and the response surface plots were provided for a user to choose an alternative. Because this Taguchi methods-based methodology is simple and effective, it is recommended for determining and optimizing a machine vision system's capability.

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Authors and Affiliations

  1. Department of Industrial Engineering, Auburn University, 207 Dunstan Hall, 36849-5346, Auburn, AL, USA

    Bernard C. Jiang & Michael Yau -Ren Shiau

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  1. Bernard C. Jiang
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  2. Michael Yau -Ren Shiau
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Jiang, B.C., Shiau, M.Y.R. A systematic methodology for determining/optimizing a machine vision system's capability. Machine Vis. Apps. 3, 169–182 (1990). https://doi.org/10.1007/BF01214429

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  • DOI: https://doi.org/10.1007/BF01214429

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