Designing morphological composite operators based on fuzzy systems

Aldo W. Morales; Sung-Jea Ko

doi:10.1117/12.144762

21 May 1993 Designing morphological composite operators based on fuzzy systems

Aldo W. Morales, Sung-Jea Ko

Proceedings Volume 1902, Nonlinear Image Processing IV; (1993) https://doi.org/10.1117/12.144762
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

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.

Citation Download Citation

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

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