Hybrid ACO algorithm for edge detection

被引：3
|
作者：
Martinez, Cristian A. [1 ]
Buemi, Maria E. [2 ]
机构：
[1] Univ Nacl Salta, Dept Informat, Av Bolivia 5150, RA-4400 Salta, CP, Argentina
[2] Univ Buenos Aires, Dept Comp, Ciudad Univ, RA-1428 Buenos Aires, CP, Argentina
来源：
EVOLVING SYSTEMS | 2021年 / 12卷 / 03期
关键词：
Algorithms; Ant colony optimization; Edge detection methods; Image processing;
D O I：
10.1007/s12530-019-09321-5
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ant colony optimization is a metaheuristic where a colony of artificial ants cooperate to find good solutions to different optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images that allow to extract relevant information. Here, an algorithm based on the ACO metaheuristic for edge detection is proposed. Using heuristic and knowledge information in the construction phase and a repair operator in the improvement phase, a binary image containing detected edges is reached. Our proposal was tested with several images in and without presence of noise. Results are competitive in terms of output images, effectiveness and CPU time.
引用
收藏
页码：849 / 860
页数：12
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