Title :
Image Classification using Chaotic Particle Swarm Optimization
Author :
Chandramouli, K. ; Izquierdo, Ebroul
Author_Institution :
Multimedia & Vision Res. Group, London Univ., UK
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;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312968
