Investigating particle swarm optimisation topologies for edge detection in noisy images

4Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper investigates the effects of applying different well-known static and dynamic neighbourhood topologies on the efficiency and effectiveness of a particle swarm optimisation-based edge detection algorithm. Our experiments show that the use of different topologies in a PSO-based edge detection algorithm does not have any significant effect on the accuracy of the algorithm for noisy images in most cases. That is in contrast to many reported results in the literature which claim that the selection of the neighbourhood topology affects the robustness of the algorithm to premature convergence and its accuracy. However, the fully connected topology in which all particles are connected to each other and exchange information performs more efficiently than other topologies in the PSO-based based edge detector. © 2011 Springer-Verlag.

Cite

CITATION STYLE

APA

Setayesh, M., Zhang, M., & Johnston, M. (2011). Investigating particle swarm optimisation topologies for edge detection in noisy images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7106 LNAI, pp. 609–618). https://doi.org/10.1007/978-3-642-25832-9_62

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free