Robust design of dilation and erosion CNN for gray scale image

Xiaoliang Zhang; Lequan Min; Min Li

doi:10.1117/12.2203549

3 December 2015 Robust design of dilation and erosion CNN for gray scale image

Xiaoliang Zhang, Lequan Min, Min Li

Proceedings Volume 9794, Sixth International Conference on Electronics and Information Engineering; 97941S (2015) https://doi.org/10.1117/12.2203549
Event: Sixth International Conference on Electronics and Information Engineering, 2015, Dalian, China

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.

Citation Download Citation

Xiaoliang Zhang, Lequan Min, and Min Li "Robust design of dilation and erosion CNN for gray scale image ", Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97941S (3 December 2015); https://doi.org/10.1117/12.2203549

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