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Proceedings Paper

Relaxation Labeling Using Modular Operators
Author(s): James S. Duncan; Werner Frei
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Paper Abstract

Probabalistic relaxation labeling has been shown to be useful in image processing, pattern recognition, and artificial intelligence. The approaches taken to date have been encumbered with computationally extensive summations which generally prevent real-time operation and/ or easy hardware implementation. This paper presents a new and unique approach to the relaxation labeling problem using modular, VLSI-oriented hierarchical complex operators. One of the fundamental concepts of this work is the representation of the probability distribution of the possible labels for a given object (pixel) as an ellipse, which may be summed with neighboring object's distribution ellipses, resulting in a new, relaxed label space. The mathematical development of the elliptical approach will be presented and compared to more classical approaches, and a hardware block diagram that shows the implementation of the relaxation scheme using VLSI chips will be presented. Final-ly, results will be shown which illustrate applications of the modular scheme, iteratively, to both edges and lines.

Paper Details

Date Published: 26 October 1983
PDF: 12 pages
Proc. SPIE 0397, Applications of Digital Image Processing V, (26 October 1983); doi: 10.1117/12.935293
Show Author Affiliations
James S. Duncan, University of Southern California School of Medicine (United States)
Werner Frei, University of Southern California School of Medicine (United States)


Published in SPIE Proceedings Vol. 0397:
Applications of Digital Image Processing V
Andre J. Oosterlinck; Andrew G. Tescher, Editor(s)

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