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Proceedings Paper

How To Select Cameras For Machine Vision
Author(s): Norman Wittels; James R. McClellan; Katherine Cushing; Willard Howard; Ann Palmer
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Paper Abstract

Solid state (CCD, CID, or multiplexed photosensor) television cameras are the most widely used input devices in machine vision, because they are relatively inexpensive, rugged, and reliable. However, the design, specification, and testing of these cameras typically are geared to their primary use in producing images that will ultimately be observed by humans; the intended applications for these cameras are as diverse as parking lot security and home entertainment. Because the video information produced by the camera is not used in the same ways by people and machine vision systems, there is no a priori reason to expect that a camera designed for one use will be optimal for another. In our work we have examined what makes a camera suitable for machine vision use. This paper describes which characteristics are important to the camera's performance machine vision applications and why. We show how these characteristics can be measured and standardized using simple tests suitable for production screening or more extensive tests suitable for use in the laboratory. Tests for important camera characteristics, including transfer function, noise, and resolution, are described and test results for representative solid state cameras are presented. Finally, we discuss how such measurements can be useful in designing or selecting the components of a machine vision system: the video capture systems, the cameras, and the image processing algorithms.

Paper Details

Date Published: 7 March 1989
PDF: 10 pages
Proc. SPIE 1005, Optics, Illumination, and Image Sensing for Machine Vision III, (7 March 1989); doi: 10.1117/12.949025
Show Author Affiliations
Norman Wittels, Worcester Polytechnic Institute (United States)
James R. McClellan, Worcester Polytechnic Institute (United States)
Katherine Cushing, Worcester Polytechnic Institute (United States)
Willard Howard, Worcester Polytechnic Institute (United States)
Ann Palmer, Worcester Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 1005:
Optics, Illumination, and Image Sensing for Machine Vision III
Donald J. Svetkoff, Editor(s)

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