基于时复用CNN模拟器的噪声图像边缘检测

Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2014-07-11 DOI:10.1109/ICCCNT.2014.6963142

V. Murugesh, V. Arthy, V. Agalya

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引用次数: 5

摘要

本文提出了一种基于细胞神经网络的含噪图像边缘检测方法。将时间复用CNN模拟器的实验结果与传统的边缘检测算子Canny和Sobel进行了比较。仿真结果表明，该模拟器能够准确地检测出噪声图像的边缘。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Edge detection of noisy images based on time-multiplexing CNN simulator

This paper presents a cellular neural network based edge detection of noisy images using Time-Multiplexing CNN Simulator. The experimental results of Time-Multiplexing CNN Simulator are compared with traditional edge detection operators Canny and Sobel. Simulation results show that the proposed simulator is accurately detecting the edge of noisy images.

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Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT)

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