A cellular fuzzy associative memory for bidimensional pattern segmentation

Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications Pub Date : 2002-07-22 DOI:10.1109/CNNA.2002.1035080

L. Carnimeo, A. Giaquinto

引用次数: 5

Abstract

In this paper a cellular fuzzy associative memory containing fuzzy rules for gray image fuzzification in automatic vision systems is developed. This cellular processor is viewed as a subsystem of a CNN-based architecture, which aims to store both bidimensional patterns and the rules to process them. After establishing the fuzzy rules which define the fuzzy associative memory for image processing, a CNN behaving as a memory is synthesized to store them. A numerical example is reported to show how the synthesized cellular FAM can process bidimensional patterns for robotic navigation purposes.

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二维模式分割的细胞模糊联想记忆

本文提出了一种包含模糊规则的元胞模糊联想记忆方法，用于自动视觉系统中灰度图像的模糊化。这种细胞处理器被视为基于cnn架构的一个子系统，其目的是存储二维模式和处理它们的规则。在建立模糊规则定义图像处理的模糊联想记忆后，合成一个作为记忆的CNN来存储这些模糊规则。通过一个数值例子，说明了合成的细胞FAM如何处理机器人导航的二维图形。

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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Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications

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