Image classification using chaotic particle swarm optimization

被引：15

作者：

Chandramouli, Krishna ^{[1
]}

Izquierdo, Ebroul ^{[1
]}

机构：

[1] Univ London, Multimedia & Vis Res Grp, Mile End Rd, London E1 4NS, England

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年

关键词：

image classification; particle swarm optimization; chaos theory; self organizing feature maps; genetic algorithm and evolutionary computation;

D O I：

10.1109/ICIP.2006.312968

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Particle Swarm Optimization is one of several metaheuristic 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.

引用

页码：3001 / +

页数：2

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