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Proceedings Paper

Designing morphological composite operators based on fuzzy systems
Author(s): Aldo W. Morales; Sung-Jea Ko
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Paper Abstract

In this paper, we introduce a method to design gray scale composite morphological operators as fuzzy neural networks. In this structure, synaptic weights are represented by a gray scale structuring element. The proposed method is a two-step procedure. First, a suitable neural topology is found through the basis functions of the composite operators. Second, a learning rule based on the average least mean square is applied where each synaptic weight is found through a back propagation algorithm. One dimensional examples are shown. This scheme can be easily extended to two dimensions.

Paper Details

Date Published: 21 May 1993
PDF: 11 pages
Proc. SPIE 1902, Nonlinear Image Processing IV, (21 May 1993); doi: 10.1117/12.144762
Show Author Affiliations
Aldo W. Morales, The Pennsylvania State Univ. (United States)
Sung-Jea Ko, Korea Univ. (South Korea)

Published in SPIE Proceedings Vol. 1902:
Nonlinear Image Processing IV
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham, Editor(s)

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