DocumentCode
2287023
Title
Composite morphological functions for DT-CNNs
Author
Brugge, M. H Ter ; Nijhuis, J.A.G. ; Spaanenburg, L.
Author_Institution
Dept of Comput. Sci., Rijksuniv. Groningen, Netherlands
fYear
2002
fDate
22-24 Jul 2002
Firstpage
587
Lastpage
594
Abstract
Mathematical morphology is a powerful means to specify image manipulations; discrete-time cellular neural networks (DT-CNN) is the fast realization. The attractive combination has been sufficiently shown for simple problems but tends to fail in efficiency for more complex ones. The paper introduces a complement and argument swap (CAS) equivalence that allows to solve an image processing problem through a small library of representative efficient designs.
Keywords
cellular neural nets; image processing; mathematical morphology; CAS equivalence; DT-CNN; complement/argument swap equivalence; composite morphological functions; discrete-time cellular neural networks; image manipulations; mathematical morphology; Cellular neural networks; Content addressable storage; Data mining; Design methodology; Image processing; Joining processes; Libraries; Morphology; Process design; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
Print_ISBN
981-238-121-X
Type
conf
DOI
10.1109/CNNA.2002.1035099
Filename
1035099
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