Can I read Detection of Continuous, Smooth and Thin Edges in Noisy Images Using Constrained Particle Swarm Optimisation on EtoBox?

Detection of Continuous, Smooth and Thin Edges in Noisy Images Using Constrained Particle Swarm Optimisation by Mahdi Setayesh; Mengjie Zhang; Mark Johnston is a scholarly article available to read on EtoBox.

What is Detection of Continuous, Smooth and Thin Edges in Noisy Images Using Constrained Particle Swarm Optimisation about?

Detecting continuous edges is a hard problem especially in noisy images. We propose an algorithm based on particle swarm optimisation (PSO) to detect continuous and smooth edges in such images. A constrained PSO-based algorithm with a new penalised objective function and two constraints is proposed to overcome noise and reduce broken edges. The new algorithm is examined and compared with a modified version of the Canny algorithm, the robust rank order (RRO)-based algorithm, and an existing PSO-based algorithm on two sets of images with different types and levels of noise. The results suggest that the new algorithm detect edges more accurately than these three algorithms and the detected edges are smoother than those detected by the previous PSO algorithm and thinner than those detected by RRO.

Author

Mahdi Setayesh; Mengjie Zhang; Mark Johnston

Publisher

ACM

Published

2011

Language

EN