Edge detection with fuzzy cellular automata transition function optimized by PSO

被引：26
|
作者：
Uguz, S. [1 ]
Sahin, U. [2 ]
Sahin, F. [2 ]
机构：
[1] Harran Univ, Dept Math, TR-63120 Sanliurfa, Turkey
[2] Rochester Inst Technol, Multi Agent Biorobot Lab, Rochester, NY 14623 USA
来源：
COMPUTERS & ELECTRICAL ENGINEERING | 2015年 / 43卷
关键词：
Cellular automata; Image processing; Edge detection; Cellular automata linear rules; ALGORITHM;
D O I：
10.1016/j.compeleceng.2015.01.017
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：180 / 192
页数：13
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