Designing morphological composite operators based on fuzzy systems

Aldo Morales, Sung Jea Ko

Research output: Contribution to journalConference article

1 Citation (Scopus)

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 will be shown. This scheme can be easily extended to two dimensions.

Original languageEnglish
Pages (from-to)280-290
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1902
DOIs
Publication statusPublished - 1993 May 21
EventNonlinear Image Processing IV 1993 - San Jose, United States
Duration: 1993 Jan 311993 Feb 5

    Fingerprint

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this