Design of discrete-time cellular neural networks based on mathematical morphology

Author

ter Brugge, M.H. ; Krol, R.J. ; Nijhuts, J.A.G. ; Spaanenburg, L.

Author_Institution

Dept. of Comput. Sci., Groningen Univ., Netherlands

fYear

1996

Firstpage

1

Lastpage

5

Abstract

Mathematical morphology is a discipline that provides a formal framework for the analysis and manipulation of images. Its theoretical foundations have been well-established in the last forty years and it has shown to be a power fool tool in the development of a large number of image processing applications. This paper shows that a lot of knowledge that is developed in the field of mathematical morphology can be applied to discrete-time cellular neural networks (DTCNNs). DTCNN equivalencies of the elementary morphological operators, which are the basic building blocks for complex image operations, are introduced and the correctness of these templates is formally proved

Keywords

cellular neural nets; discrete time systems; image representation; mathematical morphology; complex image operations; discrete-time cellular neural networks; mathematical morphology; templates; Cellular neural networks; Difference equations; Differential algebraic equations; Image analysis; Image processing; Morphology; Partial differential equations; Physics computing; Pixel; Zinc;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on

Conference_Location

Seville

Print_ISBN

0-7803-3261-X

Type

conf

DOI

10.1109/CNNA.1996.566479

Filename

566479