Integrating a-priori information in edge-linking algorithms

Aly A. Farag; Yu Cao; Yuen-Pin Yeap

doi:10.1117/12.138281

16 September 1992 Integrating a priori information in edge-linking algorithms

Aly A. Farag, Yu Cao, Yuen-Pin Yeap

Proceedings Volume 1700, Automatic Object Recognition II; (1992) https://doi.org/10.1117/12.138281
Event: Aerospace Sensing, 1992, Orlando, FL, United States

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.

Citation Download Citation

Aly A. Farag, Yu Cao, and Yuen-Pin Yeap "Integrating a priori information in edge-linking algorithms", Proc. SPIE 1700, Automatic Object Recognition II, (16 September 1992); https://doi.org/10.1117/12.138281

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