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Proceedings Paper

Edge Detection: Image-Plane Versus Digital Processing
Author(s): Friedrich O. Huck; Carl L. Fales; Stephen K. Park; Judith A. Triplett
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Paper Abstract

To optimize edge detection with the familiar Laplacian-of-Gaussian (v2G) operator, it has become common to implement this operator with a large (30-by-30 or so) digital convolution mask followed by some interpolation of the processed data to determine the zero crossings that locate edges. It is generally recognized that this large mask causes substantial blur-ring of fine detail. We show that the spatial detail can be improved by a factor of about four with either the Wiener-v2G filter or an image-plane processor. The Wiener-v2G filter minimizes the image-gathering degradations if the scene statistics are (at least approxi-mately) known and also serves as an interpolator to determine the desired zero crossings di-rectly. The image-plane processor forms the v2G response by properly combining the opti-cal design of the image-gathering system with a minimal 3-by-3 lateral-inhibitory processing mask. This approach, which is suggested by (Marr's model of) early processing in human vision, also reduces data processing by about two orders of magnitude and data transmission by up to an order of magnitude.

Paper Details

Date Published: 27 March 1987
PDF: 12 pages
Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987); doi: 10.1117/12.937724
Show Author Affiliations
Friedrich O. Huck, NASA Langley Research Center (United States)
Carl L. Fales, NASA Langley Research Center (United States)
Stephen K. Park, NASA Langley Research Center (United States)
Judith A. Triplett, Computer Sciences Corporation (United States)

Published in SPIE Proceedings Vol. 0726:
Intelligent Robots and Computer Vision V
David P. Casasent, Editor(s)

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