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
Link To Document :
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