Robust color classification using fuzzy rule-based Particle Swarm Optimization

被引：3
|
作者：
Kashanipour, Alireza
Milani, Narges Sharnshiri
Kashanipour, Amir Reza
Eghrary, Hadi Haji
机构：
来源：
CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 2, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/CISP.2008.770
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we present a novel approach for color classification in which an evolutionary algorithm optimizes a Jazzy system with least number of rules and minimum error rate by meaning of Particle Swarm Optimization (PSO) method. The aim of this work is to retrieve images according to their dominant(s) color(s) expressed through linguistic expressions, and implementation through a vision system. Fuzzy sets are defined on the H, S and L components of the HSL Color Space to provide a fuzzy logic model which aims to follow the human intuition of Color Classification. The Final system designed by this method is adaptive to continuous variable lighting according to its evolving-fuzzy nature, which is one of the challenging applications in this field.
引用
收藏
页码：110 / 114
页数：5
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