Hybridized fuzzy cellular automata thresholding algorithm for edge detection optimized by PSO

Author

Sahin, Ugur ; Sahin, Ferat ; Uguz, Selman

Author_Institution

Multi Agent Biorobotic Lab., Rochester Inst. of Technol., Rochester, NY, USA

fYear

2013

fDate

11-13 Dec. 2013

Firstpage

228

Lastpage

232

Abstract

In this paper we discuss the application of two-dimensional linear cellular automata (CA) rules with the help of fuzzy heuristic membership function to the problems of edge detection in image processing applications. We proposed an efficient and simple thresholding technique of edge detection based on fuzzy cellular automata transition rules optimized by Particle Swarm Optimization method (PSO). Finally, we present some results of the proposed linear rules for edge detection and compare with some classical results.

Keywords

cellular automata; edge detection; fuzzy set theory; particle swarm optimisation; PSO; edge detection; fuzzy heuristic membership function; hybridized fuzzy cellular automata thresholding algorithm; image processing applications; particle swarm optimization method; thresholding technique; two-dimensional linear cellular automata; Automata; Computer vision; Detectors; Image edge detection; Image segmentation; Manganese; Cellular automata; cellular automata linear rules; edge detection; image processing;

fLanguage

English

Publisher

ieee

Conference_Titel

High Capacity Optical Networks and Enabling Technologies (HONET-CNS), 2013 10th International Conference on

Conference_Location

Magosa

Print_ISBN

978-1-4799-2568-1

Type

conf

DOI

10.1109/HONET.2013.6729792

Filename

6729792