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New fuzzy model for edge detection

Bezdek, J.C., Chandrasekhar, R. and Attikiouzel, Y. (1996) New fuzzy model for edge detection. In: Proceedings of SPIE: Applications of Fuzzy Logic Technology III, Volume 2761, 10 - 12 April, Orlando, Florida pp. 11-28.

Link to Published Version: http://dx.doi.org/10.1117/12.243250
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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.

Publication Type: Conference Paper
Publisher: SPIE--The International Society for Optical Engineering
Copyright: © (1996) COPYRIGHT SPIE
URI: http://researchrepository.murdoch.edu.au/id/eprint/20630
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