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

Ákos Zarândy, André Stoffels, Tamás Roska, Leon O. Chua

Research output: Contribution to journalArticle

28 Citations (Scopus)


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
Issue number2
Publication statusPublished - Dec 1 1998



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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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