Image Classification using Chaotic Particle Swarm Optimization

Author

Chandramouli, K. ; Izquierdo, Ebroul

Author_Institution

Multimedia & Vision Res. Group, London Univ., UK

fYear

2006

Firstpage

3001

Lastpage

3004

Abstract

Particle swarm optimization is one of several meta-heuristic algorithms inspired by biological systems. The chaotic modeling of particle swarm optimization is presented in this paper with application to image classification. The performance of this modified particle swarm optimization algorithm is compared with standard particle swarm optimization. Numerical results of this comparative study are performed on binary classes of images from the Corel dataset.

Keywords

chaos; genetic algorithms; heuristic programming; image classification; particle swarm optimisation; self-organising feature maps; Corel dataset; binary image class; biological system; chaotic modeling; evolutionary computation; genetic algorithm; image classification; meta-heuristic algorithms; particle swarm optimization algorithm; self organizing feature maps; Biological systems; Chaos; Clustering algorithms; Educational institutions; Genetic algorithms; Image classification; Multidimensional systems; Particle swarm optimization; Self organizing feature maps; Wind speed; Chaos Theory; Genetic Algorithm and Evolutionary Computation; Image Classification; Particle Swarm Optimization; Self Organizing Feature Maps;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2006 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1522-4880

Print_ISBN

1-4244-0480-0

Type

conf

DOI

10.1109/ICIP.2006.312968

Filename

4107201