Designing morphological composite operators based on fuzzy systems
Aldo W. Morales, Sung-Jea Ko · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
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.