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Proceedings Paper

Integrating a-priori information in edge-linking algorithms
Author(s): Aly A. Farag; Yu Cao; Yuen-Pin Yeap
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Paper Abstract

This research presents an approach to integrate a priori information to the path metric of the LINK algorithm. The zero-crossing contours of the $DEL2G are taken as a gross estimate of the boundaries in the image. This estimate of the boundaries is used to define the swath of important information, and to provide a distance measure for edge localization. During the linking process, a priori information plays important roles in (1) dramatically reducing the search space because the actual path lies within +/- 2 (sigma) f from the prototype contours ((sigma) f is the standard deviation of the Gaussian kernel used in the edge enhancement step); (2) breaking the ties when the search metrics give uncertain information; and (3) selecting the set of goal nodes for the search algorithm. We show that the integration of a priori information in the LINK algorithms provides faster and more accurate edge linking.

Paper Details

Date Published: 16 September 1992
PDF: 15 pages
Proc. SPIE 1700, Automatic Object Recognition II, (16 September 1992); doi: 10.1117/12.138281
Show Author Affiliations
Aly A. Farag, Univ. of Louisville (United States)
Yu Cao, Univ. of Louisville (United States)
Yuen-Pin Yeap, Univ. of Louisville (United States)


Published in SPIE Proceedings Vol. 1700:
Automatic Object Recognition II
Firooz A. Sadjadi, Editor(s)

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