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Proceedings Paper

New fuzzy model for edge detection
Author(s): James C. Bezdek; Ramachandran Chandrasekhar; Yianni Attikiouzel
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Paper Abstract

We view edge detection as a sequence of four operations: conditioning, feature extraction, blending and scaling. Understanding the geometry of the feature extraction and blending functions is the key to customized edge detection models. We examine the role of each of these components, and show how they lead to the determination of input-output data for edge detecting learning models such as neural networks and fuzzy systems. An example of constructing edge images from a digitized mammogram is given to illustrate the utility of this approach.

Paper Details

Date Published: 14 June 1996
PDF: 18 pages
Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); doi: 10.1117/12.243250
Show Author Affiliations
James C. Bezdek, Univ. of West Florida (United States)
Ramachandran Chandrasekhar, Univ. of Western Australia (Australia)
Yianni Attikiouzel, Univ. of Western Australia (Australia)

Published in SPIE Proceedings Vol. 2761:
Applications of Fuzzy Logic Technology III
Bruno Bosacchi; James C. Bezdek, Editor(s)

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