Edge detection with fuzzy cellular automata transition function optimized by PSO
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 to the selected 22 images from the Berkeley …
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 to the selected 22 images from the Berkeley …
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 to the selected 22 images from the Berkeley Segmentation Dataset (BSDS) and compare with some classical Sobel and Canny results. Also, Baddeley Delta Metric (BDM) is used for the performance index to compare the results.
Elsevier
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