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Proceedings Paper

Robust design of dilation and erosion CNN for gray scale image
Author(s): Xiaoliang Zhang; Lequan Min; Min Li
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Paper Abstract

The cellular neural/nonlinear network (CNN) is a powerful tool for image and video signal processing, as well as robotic and biological visions. The designs for CNN templates are one of the important issues for the practical applications of CNNs. This paper combines two CNN to implement the Dilation CNNs and Erosion CNN for gray scale images and proposes two theorems of robustness designs. The parameters of the templates can range between a hyper plane and a hyper surface in the first quartile. The simulations have been given. The results show the effectiveness of the theoretical results to be implemented in computer simulations.

Paper Details

Date Published: 3 December 2015
PDF: 8 pages
Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97941S (3 December 2015); doi: 10.1117/12.2203549
Show Author Affiliations
Xiaoliang Zhang, Univ. of Science and Technology Beijing (China)
Lequan Min, Univ. of Science and Technology Beijing (China)
Min Li, Univ. of Science and Technology Beijing (China)


Published in SPIE Proceedings Vol. 9794:
Sixth International Conference on Electronics and Information Engineering
Qiang Zhang, Editor(s)

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