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.
|Number of pages||6|
|Journal||IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications|
|Publication status||Published - Dec 1 1998|
- Binary and gray-scale mathematical morphology, cnn, cnn universal machine, dilation, erosion, reconstruction
ASJC Scopus subject areas
- Electrical and Electronic Engineering