Implementation of binary and gray-scale mathematical morphology on the CNN universal machine

A. Zarándy, André Stoffels, T. Roska, Leon O. Chua

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

A cellular neural network(CNN)-based morphological engine is proposed. An effective implementation method of binary and grayscale erosion, dilation, and reconstruction is introduced. The binary morphological operators are successfully implemented on an actual CNN universal chip. Experimental results are shown.

Original languageEnglish
Pages (from-to)163-168
Number of pages6
JournalIEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume45
Issue number2
DOIs
Publication statusPublished - 1998

Fingerprint

Cellular neural networks
Mathematical morphology
Erosion
Engines

Keywords

  • Binary and gray-scale mathematical morphology, cnn, cnn universal machine, dilation, erosion, reconstruction

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

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title = "Implementation of binary and gray-scale mathematical morphology on the CNN universal machine",
abstract = "A cellular neural network(CNN)-based morphological engine is proposed. An effective implementation method of binary and grayscale erosion, dilation, and reconstruction is introduced. The binary morphological operators are successfully implemented on an actual CNN universal chip. Experimental results are shown.",
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