21 May 1993 Designing morphological composite operators based on fuzzy systems
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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.
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Aldo W. Morales, Sung-Jea Ko, "Designing morphological composite operators based on fuzzy systems", Proc. SPIE 1902, Nonlinear Image Processing IV, (21 May 1993); doi: 10.1117/12.144762; https://doi.org/10.1117/12.144762

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