Implementation of binary and gray-scale mathematical morphology on the CNN universal machine
Article 1998 en
Authors
ÁZ
Ákos Zarándy
AS
André Stoffels
TR
T. Roska
Abstract
1 min read
A cellular neural network(CNN)-based morphological engine is proposed. An effective implementation method of binary and gray-scale 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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