Admissible Perturbation of Demicontractive Operators within Ant Algorithms for Medical Images Edge Detection

Nowadays, demicontractive operators in terms of admissible perturbation are used to solve difficult tasks. The current research uses several demicontractive operators in order to enhance the quality of the edge detection results when using ant-based algorithms. Two new operators are introduced, χ -o...

Full description

Saved in:
Bibliographic Details
Published in:Mathematics (Basel) 2020-06, Vol.8 (6), p.1040
Main Authors: Ticala, Cristina, Zelina, Ioana, Pintea, Camelia-M.
Format: Article
Language:English
Subjects:
admissible perturbation
Algorithms
Ant Colony Optimization
Case studies
Construction
Diagnostic imaging
Edge detection
fixed point
Food science
Heuristic
Image detection
Krasnoselskij iteration
Medical imaging
Operator theory
Operators
Optimization
Perturbation
Pheromones
Statistical analysis
Technology application
Theory
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Nowadays, demicontractive operators in terms of admissible perturbation are used to solve difficult tasks. The current research uses several demicontractive operators in order to enhance the quality of the edge detection results when using ant-based algorithms. Two new operators are introduced, χ -operator and K H -operator, the latter one is a Krasnoselskij admissible perturbation of a demicontractive operator. In order to test the efficiency of the new operators, a comparison is made with a trigonometric operator. Ant Colony Optimization (ACO) is the solver chosen for the images edge detection problem. Demicontractive operators in terms of admissible perturbation are used during the construction phase of the matrix of ants artificial pheromone, namely the edge information of an image. The conclusions of statistical analysis on the results shows a positive influence of proposed operators for image edge detection of medical images.
ISSN:2227-7390
2227-7390
DOI:10.3390/math8061040