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Proceedings Paper

Adaptive Filters for Edge Detection
Author(s): Peter H. Gregson; Max S. Cynader
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Paper Abstract

Edge detection in machine vision usually consists of filtering the image with a set of circularly symmetric and/or even and odd symmetric oriented filters covering a range of spatial scales. The filters' responses at each point in the image are then thresholded either before or after being combined in some manner. Selecting functions to combine responses of filters with differing spatial scales, orientations, and symmetries is a major problem with this type of approach, as is choosing appropriate thresholds. Additionally, the computational burden has rendered the approach unfit for most practical image processing systems at this time. A new "constrained matched filter" algorithm is presented which addresses these problems. At each pixel, the algorithm computes a consistency measure and forms a template based on simple measurements of changes in intensity gradient in a small neighbourhood. Consistency is a measure of the localization of gradient changes within the neighbourhood. The location of a possible edge pixel, which need not coincide with the template center, is determined. The template is cross-correlated with the image, and the result is accumulated in an output image at the edge-pixel location previously found. The result image may be thresholded to generate a "line drawing" showing the locations of lines, step edges and roof edges.

Paper Details

Date Published: 27 March 1987
PDF: 9 pages
Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987); doi: 10.1117/12.937723
Show Author Affiliations
Peter H. Gregson, Technical University of Nova Scotia (Nova Scotia)
Max S. Cynader, Dalhousie University (Nova Scotia)

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

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