New fuzzy model for edge detection

James C. Bezdek; Ramachandran Chandrasekhar; Yianni Attikiouzel

doi:10.1117/12.243250

14 June 1996 New fuzzy model for edge detection

James C. Bezdek, Ramachandran Chandrasekhar, Yianni Attikiouzel

Proceedings Volume 2761, Applications of Fuzzy Logic Technology III; (1996) https://doi.org/10.1117/12.243250
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

James C. Bezdek, Ramachandran Chandrasekhar, and Yianni Attikiouzel "New fuzzy model for edge detection", Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); https://doi.org/10.1117/12.243250

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